NLP, transformer architectures, and machines beating humans at their own game: Jon Krohn talks to Alexander H. Miller about his work in building a machine that can outsmart humans in the game of Diplomacy by engineering powers of persuasion and collusion to its own advantage. This episode is brought to you by epic LinkedIn Learning instructor Keith McCormick(linkedin.com/learning/instructors/keith-mccormick). Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information. In this episode you will learn: • Training a natural language model to interact with Diplomacy players [05:07] • Processing speeds for a Diplomacy bot [29:32] • Using transformer architectures [37:25] • How Diplomacy AI actually works [43:25] • CICERO's potential real-world applications [55:28] • How to R&D an AI project [59:27] • How to become an AI Research Manager [1:06:12] Additional materials: www.superdatascience.com/663

Our list of the top 10 SuperDataScience podcast episodes for 2022 is here. From Pandas to causality, AI breakthroughs and data storytelling, these were your most popular episodes of the year gone by. Additional materials: www.superdatascience.com/662 Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information.

Chip Huyen, co-founder of Claypot AI and author of O'Reilly's best-selling "Designing Machine Learning Systems" is here to share her expertise on designing production-ready machine learning applications, the importance of iteration in real-world deployment, and the critical role of real-time machine learning in various applications. Technical listeners like data scientists and machine learning engineers will definitely enjoy this one! This episode is brought to you by Pathway, the reactive data processing framework (https://www.pathway.com/?from=superdatascience), and by epic LinkedIn Learning instructor Keith McCormick(linkedin.com/learning/instructors/keith-mccormick). Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information. In this episode you will learn: • Why Chip wrote 'Designing Machine Learning Systems' [08:58] • How Chip ended up teaching at Stanford [13:18] • About Chip's book 'Designing Machine Learning Systems' [21:12] • What makes ML feel like magic [30:53] • How to align business intent, context, and metrics with ML [37:55] • The lessons Chip learned about training data [42:03] • Chip's secrets to engineering good features [53:19] • How Chip optimizes her productivity [1:07:48] Additional materials: www.superdatascience.com/661

ChatGPT is well-known for its potential to disrupt the writing industry, but in what other, perhaps less explored, ways can we use the tool? In this episode, Jon Krohn outlines five critical ways that ChatGPT can augment a data scientist’s work. From generating code to acting as a translation tool for programming languages, listen in to hear why ChatGPT could become a vital part of every data scientist’s toolkit. Additional materials: www.superdatascience.com/660 Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information.

NLP practitioners: this episode is for you. From the awareness of linguistic elements and annotation to getting the necessary people in the room, Vincent Warmerdam presents to Jon Krohn a recipe for a successful project and the open-source NLP tools to get there. This episode is brought to you by epic LinkedIn Learning instructor Keith McCormick (https://linkedin.com/learning/instructors/keith-mccormick). Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information. In this episode you will learn: • How Vincent came to work with De Speld [08:57] • Vincent’s role at Explosion [18:59] • How users can apply spaCy [21:46] • Prodigy: Annotate training data more efficiently with scripts [26:28] • How to manage “skill anxiety” with Calmcode [32:32] • How Vincent fixed bad labels [42:47] • The value of understanding linguistics for NLP [54:42] • How to constrain artificial stupidity [1:02:38] Additional materials: www.superdatascience.com/659

What makes data products popular? Brian T. O'Neill, Founder and Principal of Designing for Analytics, returns to the podcast to help us crack the code on building data products that people love. Additional materials: www.superdatascience.com/658 Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information.

Data engineering educator Andreas Kretz joins Jon Krohn for a 1-hour primer that covers everything you need to know about the most in-demand role in data. From skills to tools, problem-solving processes and more, growing your knowledge of data engineering only improves your marketability, so tune in today if you're ready to future-proof your data career. This episode is brought to you by Glean (https://glean.io), the platform for data insights fast, and by epic LinkedIn Learning instructor Keith McCormick (https://linkedin.com/learning/instructors/keith-mccormick). Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information. In this episode you will learn: • Why learn data engineering? [06:55] • What is data engineering? [08:08] • What sets Senior Data Engineers apart from junior ones? [13:57] • The must-know data-engineering tools [20:26] • The right path to learn data engineering [44:24] • Are certifications worth it? [51:46] • The future of data engineering [55:24] • Andreas's career challenges [58:48] Additional materials: www.superdatascience.com/657

How to attract an AI recruiter’s attention: In this episode, Jon Krohn and Tribe AI CEO Jaclyn Rice Nelson break down the key ingredients needed to make a Tribe AI recruiter say “yes!” Get Jaclyn’s top tips for forward-thinking AI talent, the skills you need to learn, and the in-demand roles on Tribe’s list of clients. Additional materials: www.superdatascience.com/656 Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information.

Transparent data science, profitable AI, and what’s missing from a data science education: Pandata’s Data Scientist in Residence Keith McCormick and Jon Krohn discuss how “insights” can never be the end product of a data science project, how to ensure you have a specific goal at the start of a project that is related to revenue, and why there is so much miscommunication between data scientists and their clients. Exclude the C-suite at your peril! This episode is brought to you by Glean (https://glean.io), the platform for data insights, fast. Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information. In this episode you will learn: • What an Executive Data Scientist in Residence is [05:27] • What A.I. transparency is and how it relates to the field of Explainable A.I. (XAI) [17:34] • How companies can ensure they profit from AI projects [36:47] • Possible organization structures for data science teams to be profitable [1:02:41] • The current gaps in data science education [1:09:58] Additional materials: www.superdatascience.com/655

14-year-old AI prodigy Mike Wimmer joins Jon Krohn to discuss his latest projects. Whether he's using AI to help conserve the world's coral reefs or launching his new IOT-based company, Mike is an endless source of inspiration in the field of AI. Additional materials: www.superdatascience.com/654 Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information.

Carlos Aguilar, the founder and CEO of Glean, a data exploration and visualization platform, knows a thing or two about starting and growing a tech startup. After recently raising a $7 million seed round, he sits down with Jon Krohn to dive into the makings of his platform and shares tips for building a great founding team and how to delight early adopters. In this episode you will learn: • How Glean extracts actionable insights from their client's data warehouses [06:48] • What sets Glean apart from other platforms [12:43] • Glean's software stack [14:43] • Glean's recent fundraising journey [24:56] • The essential characteristics of a founding team [30:53] • How Carlos founded Glean [36:56] • Carlos's former role at Flatiron Health [40:49] • How Carlos created a robotic painter [48:57] Additional materials: www.superdatascience.com/653 Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information.

MedTech, communications technology and computer vision: In this Five-Minute Friday, Jon Krohn investigates the technology that allows patients who have lost their ability to speak via medical ventilation to communicate clearly. Additional materials: www.superdatascience.com/652 Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information.

Data visualizations, color theories and color inclusivity: In this episode, Kate Strachnyi and host Jon Krohn discuss how color can make or break your data visuals, ways to make your charts and graphs more inclusive through color, and how Kate developed the tools and techniques to nail color for your data stories in her latest book, ColorWise: A Data Storyteller’s Guide to the Intentional Use of Color. In this episode you will learn: • What a “data storyteller” is [11:01] • Why color use should always be intentional [12:52] • Is color always necessary in data visualization? [29:41] • Color selection tips for your data visuals [31:19] • Three-color scales [34:54] • How to respect individual cultures in the color choices you make [38:25] • Best tools for data visualization [54:35] Additional materials: www.superdatascience.com/651 Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information.

SparseGPT is a noteworthy one-shot pruning technique that can halve the size of large language models like GPT-3 without adversely affecting accuracy. In this episode, Jon Krohn provides an overview of this development and explains its commercial and environmental implications. Additional materials: www.superdatascience.com/650 Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information.

Looking for a short primer on Machine Learning concepts? SDS Founder Kirill Eremenko and AI expert Hadelin de Ponteves are back, joining Jon Krohn to review essential ML concepts. From classification errors to logistic regression, feature scaling, the elbow method and more. The popular data science instructors also introduce their latest course: Machine Learning in Python: Level 1. In this episode you will learn: • Kirill and Hadelin's new course [17:34] • Supervised vs unsupervised learning [26:23] • False positives and false negatives [31:21] • Logistic regression [43:00] • Holding out a set of test data [46:39] • Feature scaling [52:45] • The Adjusted R-Squared metric [59:44] • The five assumptions of linear regression [1:05:12] • The Elbow Method [1:11:41] Additional materials: www.superdatascience.com/649 Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information.

Text-to-speech gets a groundbreaking update with Microsoft’s VALL-E. On this Five-Minute Friday, Jon Krohn investigates how the Microsoft team modeled their tool to replicate natural human speech using just three seconds of a person’s voice. Additional materials: www.superdatascience.com/648 Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information.

Knowledge management, trust of AI, and job automation: Tom Davenport speaks with Jon Krohn about the organizational obstacles to adopting AI, and why the C-suite also needs to learn how to handle data. This episode is brought to you by Kolena (https://kolena.io), the testing platform for machine learning. Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information. In this episode you will learn: • Cognitive bias in understanding AI [14:13] • How AI will augment rather than replace human workers [24:27] • OpenAI and regulatory action [35:13] • Jobs that might be at risk of being automated [39:57] • The potential of citizen science in accumulating and analyzing data [1:02:18] • How AI will change the game for the C-suite [1:15:17] Additional materials: www.superdatascience.com/647

Are you still wondering how to get the most out of ChatGPT's game-changing technology? In this week's Five-Minute Friday guest episode, Jon Krohn sits down with longtime friend and e-commerce entrepreneur Zack Weinberg, to discuss the practical applications of this incredible AI tool. Additional materials: www.superdatascience.com/646 Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information.

Machine learning, security and Call of Duty collide this week as Jon Krohn sits down with Carly Taylor, Lead Machine Learning Engineer for Activision's COD franchise to discuss the importance of low-latency, the future of gaming and her favorite software packages. This episode is brought to you by Kolena (https://kolena.io), the testing platform for machine learning. Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information. In this episode you will learn: • The relationship between data science and cyber security [4:49] • The importance of low-latency for an optimal gaming experience [9:15] • The future of gaming [18:13] • Carly's thoughts on the Metaverse [25:43] • Carly’s favorite operating systems, software packages, and keyboards [30:27] • How to transition from a quantitative academic background into data science [45:28] • Why Carly is called the “Rebel Data Scientist” [53:27] • How to file a patent [57:21] Additional materials: www.superdatascience.com/645

Love and money matter in this week’s Five-Minute Friday, as Stanford University’s Myra Strober sits down with Jon Krohn to talk about her latest book, Money and Love, coauthored with Abby Davisson. In this unorthodox take on thinking with your head versus your heart, Myra and Abby address the life-changing impact that money and love have on each other and how to rethink this relationship to make better decisions. Additional materials: www.superdatascience.com/644 Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information.

AI prediction tools for antibodies and using statistics to prepare healthcare systems for pandemics: host Jon Krohn speaks with Chief Scientist of Biologics AI for Exscientia Charlotte Deane about the variety of potential partnerships between medicine and machine learning. This episode is brought to you by Kolena (https://kolena.io), the testing platform for machine learning. Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information. In this episode you will learn: • What does Biologics AI mean? [03:48] • How to use AI to predict protein structures [07:37] • What antibodies are [14:00] • Personalized Medicine is slow but A.I. can speed it up [24:36] • The future of predicting 4D protein structures [44:30] • Applications of machine learning during the pandemic [53:27] Additional materials: www.superdatascience.com/643

Looking to shake up your data science productivity in 2023? Switching to a continuous calendar can make all the difference. Jon Krohn shares his new calendar with those taking their yearly, monthly and daily planning to the next level. Additional materials: www.superdatascience.com/642 Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information.

The top data science trends of 2023 are here. Sadie St. Lawrence joins Jon Krohn to share annual predictions on the future of AI. From the data mesh to multimodal models like ChatGPT, tune in to discover what's next. This episode is brought to you by Kolena (https://kolena.io), the testing platform for machine learning. Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information. In this episode you will learn: • A recap of 2022 predictions [5:22] • Our data science trend predictions for 2023: - Data as a product [23:36] - Multimodal A.I. models [32:26] - The data mesh [42:49] - Privacy & AI Trust [50:54] - Environmental Sustainability [54:37] • Sadie's goals for 2023 [1:16:04] Additional materials: www.superdatascience.com/641

From AI trends to rediscovering how fun it is to work with colleagues ‘in person’, host Jon Krohn wraps up the year’s best SuperDataScience content and looks ahead to another year of interviews with the data science community’s brightest stars. Additional materials: www.superdatascience.com/640 Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information.

Learning Python for beginners is made fun on Mariya Sha’s YouTube and Discord channels, on which she posts hacks, breakdowns and tutorials on everything to do with the world’s most important programming language. If you’re continually frustrated by the high base level at which many ML and Python courses seem to begin, this episode is a great jumping-off point for you. This episode is brought to you by Kolena (https://kolena.io), the testing platform for machine learning. Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information. In this episode you will learn: • Why Mariya was first interested in learning Python [04:44] • The positive potential for future AI applications [12:02] • Useful broadcasting software [23:09] • The importance of productivity hacking in data science [34:13] • The ethical problems of web scraping [38:45] • Mariya’s favorite Python libraries [53:48] • What excites Mariya about the future of NLP [1:13:53] • Mariya’s favorite software tools [1:15:23] Additional materials: www.superdatascience.com/639

OpenAI's ChatGPT helps us generate a special holiday greeting this week. Tune in to hear the festive message that this impressive natural language generating algorithm churned out as we close out the year. Additional materials: www.superdatascience.com/638 Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information.

It's all about data visualization this week as Jon Krohn welcomes Ann K. Emery, data visualization designer and owner of Depict Data Studio, to the show. If you want to learn data viz best practices, tips and tricks and reporting how-tos, make some time to tune in today! This episode is brought to you by Kolena (https://kolena.io), the testing platform for machine learning. Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information. In this episode you will learn: • What data storytelling is [03:40] • Pinpoints of data visualization [10:38] • Best practices for data visualization [23:41] • Surprising spreadsheet tricks [30:51] • When static dashboards are more effective than interactive ones [43:30] • Ann's top tips for presenting data in a slideshow [48:07] Additional materials: www.superdatascience.com/637

Digital literacy and data bias: Can one reduce or even eradicate the other? Law professor Orly Lobel speaks with SDS host Jon Krohn about Orly’s latest book, The Equality Machine, which offers an optimistic look into the future of AI and data mining. Additional materials: www.superdatascience.com/636 Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information.

Hand labeling data and information bias: Jon Krohn speaks with Watchful CEO Shayan Mohanty about the pitfalls of data analysis when bias comes into the equation (spoiler alert: it always does), the importance of the Chomsky hierarchy in data management, and the importance of simulation engines for returning real-time results to users. This episode is brought to you by Iterative (https://iterative.ai), your mission control center for machine learning. Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information. In this episode you will learn: • Why bias in general is good [04:06] • The arguments against hand labeling [09:47] • How Shayan solves the problem of labeling at his company [24:26] • Misconceptions concerning hand-labeled data [43:25] • What the Chomsky hierarchy is [52:38] • Watchful’s high-performance simulation engine [1:04:51] • What Shayan looks for in his new hires [1:08:15] Additional materials: www.superdatascience.com/635

Data scientist and author Serg Masís joins Jon Krohn for a Five-Minute Friday episode that touches on model error analysis. Learn how this process can improve your models and discover a helpful tool that expedites this critical process. Additional materials: www.superdatascience.com/634 Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information.

This week's episode is all about Responsible Decentralized Intelligence as award-winning professor and tech entrepreneur, Dawn Song, joins Jon Krohn to help us explore this exciting topic in-depth. This episode is brought to you by Iterative (https://iterative.ai), your mission control center for machine learning. Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information. In this episode you will learn: • What is decentralized intelligence? [3:46] • Dawn’s Responsible Data Economy collaboration with Meta AI [11:31] • How homomorphic encryption, differential privacy, and multi-party computation can work together [16:22] • How PrivateSQL makes differential privacy easy to use [22:54] • The relationship between deep learning and federated learning [37:55] • What is a responsible data economy [42:13] Additional materials: www.superdatascience.com/633

Liquid neural networks are a type of bio-inspired machine learning set to make a huge impact in the field of data analytics. On this week’s Five-Minute Friday, Jon Krohn speaks with Pathway.com Co-Founder Dr. Adrian Kosowski about the development of this new type of network and what this means for the future of data. Additional materials: www.superdatascience.com/632 Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information.

Interview success, funny memes about data, and stakeholder management: Jon Krohn speaks with Luke Barousse, a full-time YouTuber who produces content to help aspiring data scientists. First, Jon and his guest go underwater to find out how data science can help you while working on a submarine before they emerge onto Luke’s YouTube channel. There, he discloses all the helpful hacks for data science beginners—with a generous helping of humor! As founder of MacroFit, a data-driven company that helps with meal planning, Luke is no stranger to portion sizes… This episode is brought to you by Iterative (https://iterative.ai), your mission control center for machine learning. Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information. In this episode you will learn: • Where Luke gets his inspiration for making YouTube videos [04:46] • How Luke got into creating comedy skits [08:21] • Luke’s favorite Python libraries for web scraping [14:41] • Incorrect assumptions that aspiring data scientists make [15:54] • The best time to use Power BI [19:15] • The biggest mistakes Luke made in his data science career [22:17] • Luke’s experience as a submariner and how it helped him in his data analyst career [38:13] • The must-have skills for entry-level data analyst roles [43:46] Additional materials: www.superdatascience.com/631

Jon Krohn sits with Dr. Dan Shiebler at the Open Data Science Conference (ODSC) to dive into the critical components of building resilient machine learning. Additional materials: www.superdatascience.com/630 Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information.

Has the term developer advocacy ever left you scratching your head? This week data science developer advocate for JetBrains, Dr. Jodie Burchell, joins Jon Krohn to shed light on her responsibilities and why it's a role you might want to consider. Jodie also dives into building reproducible data science workflows and the keys to working effectively with real-world data. This episode is brought to you by Iterative (https://iterative.ai), the open-source company behind DVC. Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information. In this episode you will learn: • Jodie’s background in psychology [2:19] • Jodie's tips for real-world data preparation [6:52] • Tour JetBrains' developer tools: PyCharm, DataSpell and Datalore [10:38] • What is a data science developer advocate? [38:44] • The books that Jodie's co-authored [46:15] • Jodie's favorite Python libraries [58:30] • How to have reproducible data science workflows [1:01:33] Additional materials: www.superdatascience.com/629

On this episode of Five-Minute Friday, Jon Krohn speaks from the Open Data Science Conference (ODSC). There, he sits down with author and data scientist Keith McCormick to discuss the conference’s key trend: learning the importance of trust in the relationship between humans and algorithms. Additional materials: www.superdatascience.com/628 Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information.

Jon Krohn speaks with Erin LeDell, H2O.ai’s Chief Machine Learning Scientist. They investigate how AutoML supercharges the data science process, the importance of admissible machine learning for an equitable data-driven future, and what Erin’s group Women in Machine Learning & Data Science is doing to increase inclusivity and representation in the field. This episode is brought to you by Datalore (https://datalore.online/SDS), the collaborative data science platform. Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information. In this episode you will learn: • The H2O AutoML platform Erin developed [07:43] • How genetic algorithms work [19:17] • Why you should consider using AutoML? [28:15] • The “No Free Lunch Theorem” [33:45] • What Admissible Machine Learning is [37:59] • What motivated Erin to found R-Ladies Global and Women in Machine Learning and Data Science [47:00] • How to address bias in datasets [57:03] Additional materials: www.superdatascience.com/627

Word tokenization, character tokenization and subword tokenization go head-to-head this week as Jon Krohn delivers a mini-bootcamp on the NLP-related process. Additional materials: www.superdatascience.com/626 Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information.

Chainalysis' Director of Research, Kim Grauer joins Jon Krohn to explore the state of economic-data analysis on the blockchain. This episode is brought to you by Datalore (https://datalore.online/SDS), the collaborative data science platform. Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information. In this episode you will learn: • Kim's role as Director of Research [5:02] • The unique real-time economic-data analytics of the blockchain [13:07] • How ML can predict patterns of criminal activity on the blockchain [18:56] • Interesting use cases of ML for crime investigation [29:37] • The tools and approaches Kim uses daily [47:44] • The future of crypto, blockchains, and data science [50:54] • Why a data science bootcamp helps people break into data science [53:42] Additional materials: www.superdatascience.com/625

On this week’s Five-Minute Friday, Jon Krohn investigates Imagen Video, Google’s latest model for making video art out of text prompts. Recently published, this text-to-image converter now competes against already strong competitors on the scene like DALL-E 2. Unlike DALL-E 2, it returns moving images or time-based media. Tune in to hear Jon explain the technology that made Imagen Video the tech giant’s shiniest new tool to date. Additional materials: www.superdatascience.com/624 Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information.

Jon Krohn speaks with Shashank Kalanithi, the man who makes a sport out of YouTube and data analytics out of sports. Listen in as he talks about how he got started producing YouTube videos on data science, the essential differences between data science roles, and how data could shape the future of the sports industry. This episode is brought to you by Datalore (https://datalore.online/SDS), the collaborative data science platform. Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information. In this episode you will learn: • What motivated Shashank to start his YouTube channel [04:31] • The must-have technical skills for every data scientist [16:59] • The soft skills needed for data science [20:52] • The differences between data analyst, data scientist and data engineer [24:26] • How data are currently being applied in the sports industry [38:38] • The “needs” divide between digital native and traditional companies [45:34] Additional materials: www.superdatascience.com/623

Is burnout on the horizon for you and your team? Christina Maslach, author of the new book "The Burnout Challenge," joins Jon Krohn to help us identify the common signs of looming burnout while steering us in a healthier direction. Additional materials: www.superdatascience.com/622 Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information.

Cryptocurrency and blockchain take center stage this week as we welcome Chief Economist at Chainalysis, Philip Gradwell, to discuss the data science applications in this exciting field. This episode is brought to you by Datalore (https://datalore.online/SDS), the collaborative data science platform, by Zencastr (zen.ai/sds), the easiest way to make high-quality podcasts, and by Bunch (superdatascience.com/bunch), the AI driven leadership coach. Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information. In this episode you will learn: • What the role of a chief economist entails [5:50] • What are blockchains and cryptocurrency? [8:23] • How analyzing cryptocurrencies differs from established fiat currencies [12:48] • Philip's work at Chainalysis [26:07] • Philip's crypto data analytics pipeline [34:48] • How Philip develops data products for a wide range of users [46:18] • How the blockchain facilitates innovative computing and machine learning technologies [51:52] • What Philip looks for in the data scientists he hires [1:04:59] Additional materials: www.superdatascience.com/621

What’s your secret to superb audio recognition? Whisper it. We mean that literally—Whisper is the latest in OpenAI’s growing suite of models aimed to benefit humanity. On this episode of Five-Minute Friday, host Jon Krohn reviews OpenAI’s latest model, Whisper. This tool will vastly improve the way human speech is recognized and converted to text. Jon gets under the hood to show how the team managed to get such a powerfully accurate recognition model. Listen to the episode and find out how you can try it yourself, for free! Additional materials: www.superdatascience.com/620 Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information.

Jon Krohn speaks with Erik Bernhardsson, the man who invented Spotify’s original music recommendation system. They address the different ways to interview a data science candidate, how to deploy a data model into the cloud, and the approach he took that made Spotify go from a digital music startup to an AI-driven streaming giant. This episode is brought to you by Datalore (https://datalore.online/SDS), the collaborative data science platform, by Zencastr (zen.ai/sds), the easiest way to make high-quality podcasts, and by Bunch (superdatascience.com/bunch), the AI driven leadership coach. Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information. In this episode you will learn: • The data problem that Erik’s company Modal Labs solves [04:32] • Erik’s prolific blogging career [09:15] • Opportunities for making data teams more efficient and productive [14:42] • Erik’s views on interviewing data scientists and software developers [20:18] • Erik’s tips and tricks for data science interviewees [31:35] • How Erik built Spotify’s original music recommendation system [38:58] • Applying vectors to other tools, and opportunities for working with vectors [47:45] • Using Annoy to search across vectors [50:57] • Building Python module Luigi for Spotify [55:20] • The tools that Erik loves to work with [1:06:23] Additional materials: www.superdatascience.com/619

Telic and atelic activities take center stage this week as Jon Krohn contemplates how our daily actions contribute to our overall sense of fulfillment. Additional materials: www.superdatascience.com/618 Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information.

Dr. Sean Taylor, Co-Founder and Chief Scientist of Motif Analytics, joins Jon Krohn this week for yet another perspective on causal modeling. Tune in for a great conversation that covers large-scale causal experimentation, Information Systems, Bayesian parameter searches, and more. This episode is brought to you by Datalore (https://datalore.online/SDS), the collaborative data science platform, and by Zencastr (zen.ai/sds), the easiest way to make high-quality podcasts. Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information. In this episode you will learn: • Sean on his new venture, Motif Analytics [4:23] • The relationship between causality and sequence analytics [15:26] • Sean's data science work at Lyft [22:21] • The key investments for large-scale causal experimentation [27:25] • Why and when is causal modeling helpful [32:34] • Causal modeling tools and recommendations [36:52] • Facebook's Prophet automation tool for forecasting [40:02] • What Sean looks for in data science hires [50:57] • Sean on his PhD in Information Systems [53:34] Additional materials: www.superdatascience.com/617

10,000 hours of study: Will it make you an expert? On this episode of Five-Minute Friday, host Jon Krohn explores whether increasing your skills is just a numbers game or if there is more to becoming proficient in your area of interest, whether that’s flute playing or data wrangling. Additional materials: www.superdatascience.com/616 Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information.

“Being a great data scientist” and “being great at a data science interview” are not one and the same. Jon Krohn speaks with Nick Singh about how to strengthen your interviewee skills, and how you can even beat out more senior competition to land a coveted data science role. This episode is brought to you by Datalore (https://datalore.online/SDS), the collaborative data science platform, and by Zencastr (zen.ai/sds), the easiest way to make high-quality podcasts. Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information. In this episode you will learn: • Nick’s inspiration for writing his bestselling book, Ace the Data Science Interview [06:21] • Why Nick believes in being a work generalist [12:37] • How DataLemur supports emerging data scientists for free [15:43] • Why Nick started DataLemur off the back of his book [21:31] • Portfolio essentials for any data scientist [22:36] • The three most common things data scientists get wrong at the interview [24:33] • How data science introverts can shift their mindset about self-promotion [37:58] • Great responses to end your data science interview on the right foot [42:21] Additional materials: www.superdatascience.com/615

World-leading futurist, author and entrepreneur, Ross Dawson joins us for the first of our extended Five-Minute Friday episodes. As information overwhelm becomes increasingly unavoidable, Dawson is here to share the five powers from his new book 'Thriving on Overload', to help us transition from overwhelm into abundance. Additional materials: www.superdatascience.com/614 Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information.

Dr. Emre Kiciman, Senior Principal Researcher at Microsoft Research joins the podcast to share his world-leading knowledge on causal machine learning. This episode is brought to you by Datalore (https://datalore.online/SDS), the collaborative data science platform, and by Zencastr (zen.ai/sds), the easiest way to make high-quality podcasts. Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information. In this episode you will learn: • What is causal machine learning? [5:52] • Causal machine learning vs correlational machine learning [10:10] • Emre’s DoWhy open-source library [16:17] • The four key steps of causal inference [21:24] • How and why Emre’s key steps of causal inference will impact ML [26:36] • Emre's thoughts on the future of causal inference and AGI [34:09] • How Emre leverages social media data to solve social problems [38:36] • What's next for Emre's research [46:02] • The software tools Emre highly recommends [55:16] • What he looks for in the data science researchers he hires [58:45] Additional materials: www.superdatascience.com/613

Some exciting changes are coming to our popular Five-Minute Friday series! From longer episodes to new guests, tune in to hear what's next. Additional materials: www.superdatascience.com/612 Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information.

Dr. Ken Stanley, a world-leading expert on Open-Ended AI and author of the genre-bending book "Why Greatness Cannot be Planned," joins Jon Krohn for a discussion that has the potential to shift your entire view on life. Tune in now to learn more about the complex topics of genetic ML algorithms, the Objective Paradox, Novelty Search, and so much more. This episode is brought to you by Zencastr (zen.ai/sds), the easiest way to make high-quality podcasts. Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information. In this episode you will learn: • Ken on his book 'Why Greatness Cannot Be Planned" and the Objective Paradox [4:15] • The Novelty Search approach [24:14] • How open-ended algorithms like Novelty Search can be stopped from doing something potentially dangerous [1:00:00] • The future of open-ended AI and its intimate relationship with Artificial General Intelligence [1:07:34] • Ken's new company [1:13:34] • How AI could transform life for humans in the coming decades [1:18:29] Additional materials: www.superdatascience.com/611

On this episode of Five-Minute Friday, host Jon Krohn shares his life motto, “Who dares, wins”, and the sentiment behind it: that to get anywhere in life, it is first necessary to try. Jon believes that “daring”, in this instance, simply means taking action when we have a good idea or when a new opportunity becomes available. Listen to the end for constructive advice on how to be daring in your own life right now. Additional materials: www.superdatascience.com/610 Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information.

Jon Krohn speaks with Zhamak Dehghani, the empathetic technologist who coined the term “data mesh”. They explore what a data mesh is, and how its approach toward secure interconnectivity will help solve a roster of data-led business problems. This episode is brought to you by Zencastr (zen.ai/sds), the easiest way to make high-quality podcasts. Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information. In this episode you will learn: • The importance of data meshes [3:29] • How standardizing database interfaces helps tech giants like Amazon [6:40] • Current challenges with data meshes [9:33] • How data meshes give users the freedom to work with data [17:09] • The missing piece of the puzzle for data meshes [22:11] • How data meshes connect with the metaverse and Web3 [33:18] • The times when data meshes aren’t fit for purpose [42:24] Additional materials: www.superdatascience.com/609

Dr. Jennifer Hill, Professor of Applied Statistics at New York University, joins Jon this week for a discussion that covers causality, correlation, and inference in data science. This episode is brought to you by Pachyderm, the leader in data versioning and MLOps pipelines and by Zencastr (zen.ai/sds), the easiest way to make high-quality podcasts. In this episode you will learn: • How causality is central to all applications of data science [4:32] • How correlation does not imply causation [11:12] • What is counterfactual and how to design research to infer causality from the results confidently [21:18] • Jennifer’s favorite Bayesian and ML tools for making causal inferences within code [29:14] • Jennifer’s new graphical user interface for making causal inferences without the need to write code [38:41] • Tips on learning more about causal inference [43:27] • Why multilevel models are useful [49:21] Additional materials: www.superdatascience.com/607

Company meetings should be held to solve problems. So, why do we often feel like the weekly stand-ups and check-ins are a waste of everyone’s time? On this episode of Five-Minute Friday, host Jon Krohn brings his habit-making practices into the dreaded meeting room. Make every meeting productive and positive with his five-step method for assigning deliverables. Additional materials: www.superdatascience.com/608

Four thousand weeks equate to roughly 80 years—a lifetime for those of us lucky enough to get there. What do we choose to do with this time? How can we stop ourselves from feeling like time in general is slipping away? In this episode, host Jon Krohn reviews the book Four Thousand Weeks: Time Management for Mortals by journalist Oliver Burkeman. He outlines how he has personally benefited from this essential reflection on our thirst for productivity and efficiency. Additional materials: www.superdatascience.com/606

Kian Katanforoosh, CEO of Workera and Lecturer at Stanford University, joins Jon Krohn to reveal the tools, frameworks, and machine learning models that power his platform and remote team. In this episode you will learn: • What a skills intelligence platform is [3:11] • How mentorship can be life-changing [7:45] • Four ways that ML drives Kian’s skills intelligence platform [10:57] • Kian's day-to-day responsibilities as the CEO of Workera [21:00] • What frameworks and software languages Kian and his team selected for building their platform and why [24:20] • What Kian looks for in the data scientists and software engineers he hires [31:48] • Kian’s Stanford Deep Learning class and mentors [34:58] • How Kian’s passion for EdTech began [42:47] Additional materials: www.superdatascience.com/605

During this week's Five-Minute Friday episode features, Jon explores recent groundbreaking developments in nuclear fusion –ignition–and what that signals for the future. Additional materials: www.superdatascience.com/604

Christina Stathopoulos, Analytical Lead for Waze and Adjunct Professor at IE Business School, joins the podcast to shed light on her work with geospatial data and how she nurtured an entire data career while abroad in Spain. In this episode you will learn: • Christina's tips on navigating an unconventional path into a data career [3:05] • Geospatial data and open-source packages for working with it [10:08] • Guidance to help women and other underrepresented groups to thrive in tech [22:28] • The hard and soft skills most essential to success in a data role today [39:26] • Christina’s #bookaweekchallenge and the top data-centric book recommendations [43:28] Additional materials: www.superdatascience.com/603

Inspired by a quote from by science fiction writer, Teresa Nielsen Hayden, Jon Krohn reflects on the notion of living in ancient times and the machine learning-related implications that arise from this perspective. Additional materials: www.superdatascience.com/602

This week, Sarah Catanzaro, General Partner at Amplify Partners joins Jon for an episode that dives into the venture capital side of data science. Learn how to fund your data science business idea, take note of what start-ups can do to survive or raise capital in the current economic climate, and discover how to break into the field of venture capital yourself. In this episode you will learn: • Angel vs. venture capital vs. private equity investment [7:27] • How early-stage investment is made prior to a firm having product-market fit [14:33] • How to pick winners in early-stage investments [28:08] • Tricks to accelerating from a data science idea to obtaining funding [36:21] • Observational causal inference [44:01] • How to get involved in venture capital [47:37] Additional materials: www.superdatascience.com/601

Rest and relaxation await as Steve Fazzari joins us this week for a special edition of the podcast! Tune in for a rejuvenating session of Yoga Nidra led beautifully by the expert. Additional materials: www.superdatascience.com/600

This week, Mikiko Bazeley, Senior Software Engineer at Mailchimp joins the podcast to share her in-depth knowledge of MLOps: Machine Learning Operations. Tune in to hear her discuss what it entails, why it's so critical for the efficiency of any data science team, and the most important tools you need to master for career success in this field. In this episode you will learn: • What MLOps is [11:40] • Mikiko’s role at Mailchimp and why MLOps is critical for the efficiency of any data science team [27:11] • The three most important MLOps tools [32:15] • The six most essential MLOps skills for data scientists [47:01] • The key factors Mikiko looks when hiring engineers [1:07:31] • Mikiko’s productivity tricks for balancing software engineering, content creation, and her athletic pursuits [1:13:20] Additional materials: www.superdatascience.com/599

Ben Taylor makes a fourth appearance on Five-Minute Friday to discuss the best ways to introduce STEM to children. Tune in to hear the many ways in which he thinks STEM education will evolve in the future. Additional materials: www.superdatascience.com/598

Dr. Miles Brundage, Head of Policy Research at OpenAI, joins Jon Krohn this week to discuss AI model production, policy, safety, and alignment. Tune in to hear him speak on GPT-3, DALL-E, Codex, and CLIP as well. In this episode you will learn: • Miles’ role as Head of Policy Research at OpenAI [4:35] • OpenAI's DALL-E model [7:20] • OpenAI's natural language model GPT-3 [30:43] • OpenAI's automated software-writing model Codex [36:57] • OpenAI’s CLIP model [44:01] • What sets AI policy, AI safety, and AI alignment apart from each other [1:07:03] • How A.I. will likely augment more professions than it displaces them [1:12:06] Additional materials: www.superdatascience.com/597

Ben Taylor returns for a third Five-Minute Friday episode! This week, he looks ahead and digs into what we can expect from the A.I. platforms of the future. Additional materials: www.superdatascience.com/596

Tune in as Joe Reis and Matt Housley, co-founders of Ternary Data and co-authors of the book “Fundamentals of Data Engineering” join Jon Krohn to discuss major undercurrents across the data engineering lifecycle, and their top tools and techniques. In this episode you will learn: • What is data engineering? [3:55] • Why Joe and Matt identify as “recovering data scientists” [6:12] • What kinds of people tend to become data scientists vs. data engineers [10:38]? • Key components of Joe and Matt’s book [26:31] • Major undercurrents across the data engineering lifecycle [28:26] • The most under-utilized tool in a data engineer's toolbox [34:39] • How there are tradeoffs in any data pipeline latency considerations, but faster is typically the default assumption [38:55] • Joe and Matt’s favorite data engineering tools and techniques [43:39] Additional materials: www.superdatascience.com/595

This week, Jon Krohn and A.I. industry veteran Ben Taylor discuss the driving factors that push CEOs to prioritize A.I. over other technologies. Additional materials: www.superdatascience.com/594

Jon welcomes Professor Philip Bourne, Founding Dean of the School of Data Science at the University of Virginia to discuss his biomedical data science research, the importance of open-source and open-access within the industry and the data science skills you need to succeed today. In this episode you will learn: • Why Philip founded a School of Data Science [6:08] • How computing and data science have evolved across academic departments [15:55] • The improvements needed in higher education [26:44] • The most important data science skills for academia and industry and the 4+1 model [36:49] • Philip’s biomedical data science research and its fascinating practical applications [43:24] • The essential roles of open-source code and open-access publishing in data science [1:01:27] Additional materials: www.superdatascience.com/593

In this episode, Jon Krohn welcomes A.I. industry veteran Ben Taylor to discuss how to sell multimillion dollar A.I. contracts. Tune in to hear why trust and proof of value are some of the critical steps in his sales process. Additional materials: www.superdatascience.com/592

Mars Buttfield-Addison, PhD Candidate at the University of Tasmania, joins Jon Krohn for a high-energy episode covering everything from Machine Learning simulations to Swift, space junk, and more! In this episode you will learn: • What simulations and synthetic data are, and why they can be invaluable for real-life applications [5:47] • How simulated bots can solve any problem [9:07] • Practical uses of simulated data [21:49] • Why the mobile operating system language Swift is interesting for A.I. [25:46] • Why it's critical to track the amount of junk in space [35:47] • Whether programming or statistical skills are more important in data science [47:05] • What it’s like creating video games in a "secret" games lab [56:45] • Why you might want to do a data science internship in industry before pursuing in academia [ 1:01:54] Additional materials: www.superdatascience.com/591

In this episode, Jon continues his two-part series on artificial general intelligence (AGI) and why we are unlikely to realize it anytime soon. Listen in as Jon reviews Meta's Yann LeCun's seven-part perspective on the topic. Additional materials: www.superdatascience.com/590

Hilary Mason, Co-Founder and CEO of Hidden Door, joins Jon Krohn for a live discussion that explores narrative A.I., emerging ML techniques, and how her OSEMN data science process developed. In this episode you will learn: • How narrative A.I. can assist creativity [5:14] • How to build ML products that have no quantitative error function to optimize [10:31] • How to ensure creative A.I. systems do not output non-sense or explicit content [16:58] • Hilary's OSEMN data science process [21:05] • The emerging ML technique she’s most excited about [24:58] • What it takes to be successful as CEO of an early-stage A.I. company [27:20] • What she looks for in engineering hires [32:28] • How she’s hopeful A.I. will transform our lives for the better in the decades to come [38:48] Additional materials: www.superdatascience.com/589

In this episode, Jon kicks off a two-part series that sees him explore the popular topic of artificial general intelligence and why it might–or might not–be only a few years away. Listen in as Jon explains the several reasons why he doesn't believe that AGI is nigh. Additional materials: www.superdatascience.com/588

Mark Freeman, Senior Data Scientist at Humu, joins Jon Krohn to talk about all things data engineering and offers listeners some critical tips for their data science career journey – from what it takes to get promoted to his number one tip for getting hired at a fast-growing capital-backed startup. In this episode you will learn: • How Humu leverages data and machine learning to improve workplace behaviors [10:38] • What is data engineering? [14:21] • What it takes to get promoted into more senior data science roles [20:55] • The differences between junior, senior, and staff data scientists [30:21] • Mark’s top tools for data extraction, modeling, and pipeline engineering [37:08] • Mark’s number one tip for getting hired at a fast-growing venture capital-backed startup [53:10] • Why all data scientists should be interested in Web3 [1:11:53] Additional materials: www.superdatascience.com/587

In this episode, Jon dives into the popular topic of social media and its impact on his productivity. Tune in to hear how minimizing the use of social media can positively impact your days, mental health and work. Additional materials: www.superdatascience.com/586

In this episode, Dr. Thomas Wiecki, Core Developer of the PyMC Library and CEO of PyMC Labs, joins Jon for a masterclass in Bayesian statistics. Tune in to hear about PyMC, and discover why Bayesian statistics can be more powerful and interpretable than any other data modeling approach. In this episode you will learn: • What Bayesian statistics is [7:30] • Why Bayesian statistics can be more powerful and interpretable than any other data modeling approach [17:20] • How PyMC was developed [20:41] • Commercial applications of Bayesian stats [43:07] • How to build a successful company culture [1:03:14] • What Thomas looks for when hiring [1:11:13] • Thomas’s top resources for learning Bayesian stats yourself [1:13:57] Additional materials: www.superdatascience.com/585

In this episode, Jon reviews the remarkable natural language model Codex by OpenAI. Learn why it has amassed a waitlist and how you can leverage its practical applications in your work. Additional materials: www.superdatascience.com/584

In this episode, natural language processing (NLP) expert and Lead Data Scientist at CB Insights, Rongyao Huang, joins Jon Krohn to discuss NLP. Listen in for a thorough review of the field over the past decade and how the coming iron age of NLP will help us overcome the limitations of today's approaches. In this episode you will learn: • The evolution of NLP techniques over the past decade [4:14] • What's next in the coming iron age of NLP [35:33] • Rongyao’s Bauhaus-inspired model for effective data science [43:12] • Rongyao's long-term career pathfinding framework [51:50] • Rongyao’s top tips for staying sane while juggling career and family [1:00:30] Additional materials: www.superdatascience.com/583

In this episode, Jon wraps up his three-part series on business value and machine learning. Listen in as he explains why starting with simple models is best, and why speed is likely more important to your users than accuracy. Additional materials: www.superdatascience.com/582

In this episode founding Editor-in-Chief of the Harvard Data Science Review and Professor of Statistics at Harvard University, Prof. Xiao-Li Meng, joins Jon Krohn to dive into data trade-offs that abound, and shares his view on the paradoxical downside of having lots of data. In this episode you will learn: • What the Harvard Data Science Review is and why Xiao-Li founded it [5:31] • The difference between data science and statistics [17:56] • The concept of 'data minding' [22:27] • The concept of 'data confession' [30:31] • Why there’s no “free lunch” with data, and the tricky trade-offs that abound [35:20] • The surprising paradoxical downside of having lots of data [43:23] • What the Bayesian, Frequentist, and Fiducial schools of statistics are, and when each of them is most useful in data science [55:47] Additional materials: www.superdatascience.com/581

In this episode, Jon resumes his series on strategies for getting business value from machine learning. Part one saw him review several ways to identify a commercial problem before starting data collection or ML model development. And now, in part two, Jon digs into the data collection process. Additional materials: www.superdatascience.com/580

In this episode, the CEO of Overjet, Dr. Wardah Inam, joins Jon Krohn to discuss the classification and quantification of dental diagnoses with computer vision, her data labeling challenges, and tips for building a successful A.I. business. In this episode you will learn: • How Overjet leverages computer vision to qualify and quantify dental diagnoses [5:11] • How A.I. solutions reduce the under-diagnosis of common diseases like periodontal disease [8:15] • Overjet's particular ML challenges within the dental industry [15:45] • Wardah's experience in introducing A.I. to the dental industry [20:12] • Wardah's tips for building a successful A.I. business [23:34] • What she looks for in the data scientists and software engineers she hires [39:36] Additional materials: www.superdatascience.com/579

In this episode, Jon kicks off a new Five-Minute Friday series that explores the strategies for getting business value from machine learning. Part one sees him review several ways to identify a commercial problem before starting data collection or ML model development. Additional materials: www.superdatascience.com/578

In this episode, the former CEO and co-founder of Onfido, an AI-based ID verification, joins Jon Krohn to discuss his path to start-up success. Tune in to hear valuable information from Husayn Kassai. In this episode you will learn: • How Husayn's start-up journey began [5:55] • How Husayn determined that his challenge could be solved by machine vision [11:18] • Onfido's initial seed stages [18:23] • Launching and scaling your start-up in the U.S. market [22:00] • The most important component in building the best product [26:30] • Husayn's latest start-up [28:52] • Husayn’s startup project decision-making process [37:49] • Choosing your co-founding team [44:04] Additional materials: www.superdatascience.com/577

Hollywood has officially fallen for the drama of tech startups! Tune in to hear Jon Krohn review the small-screen adaptations of WeWork (WeCrashed), Uber (Super Pumped), and Theranos (The Dropout). Additional materials: www.superdatascience.com/576

In this episode, the Director of Architecture at NVIDIA, Dr. Magnus Ekman, joins Jon Krohn to discuss how machine learning, including deep learning, can optimize computer hardware design. The pair also review his exceptional book 'Learning Deep Learning.' In this episode you will learn: • What hardware architects do [10:15] • How ML can optimize hardware speed [ 13:19] • Magnus’s Deep Learning Book [21:14] • Is understanding how ML models work important? [36:16] • Algorithms inspired by biological evolution [41:25] • How artificial general intelligence won’t be obtained by increasing model parameters alone [51:24] • Why there will always be a place for CNNs and RNNs [54:51] • How people can "transition" realistically into ML [1:09:15] Additional materials: www.superdatascience.com/575

In this episode, Jon shares how the right music can power your productivity. It's no secret that he's a big fan of 'deep work,' but this week, he opens up about the artists, sites, and playlists that propel his productivity to new levels. Additional materials: www.superdatascience.com/574

In this episode, co-founder and CEO of Linea, Dr. Doris Xin, joins Jon Krohn to discuss how automating ML model deployment delivers groundbreaking change to data science productivity, and shares what it's like being the CEO of an exciting, early-stage tech start-up. In this episode you will learn: • How Linea reduces ML model deployment down to a couple of lines of Python code [5:14] • Linea use cases [11:30] • How DAGs can 10x production workflow efficiency [22:12] • ML model graphlets and reducing wasted computation [24:14] • What future Doris envisions for autoML [35:23] • Doris’s day-to-day life as a CEO of an early-stage start-up [42:43] • What Doris looks for in the engineers and data scientists that she hires [52:21] • The future of Data Science and how to prepare best for it [53:58] Additional materials: www.superdatascience.com/573

In this episode, Jon shares his habit of blocking out two hours in his mornings that are free from email and social media distractions. Tune in to learn how this habit helps him deeply focus on his most delightful tasks of the day. Additional materials: www.superdatascience.com/572

Einblick co-founder and associate professor at MIT, Tim Kraska, joins Jon Krohn to discuss no-code collaboration tools for data science and uncovers the clever database and machine learning tricks under the hood of the visual data computing platform. In this episode you will learn: • The inspiration behind Einblick [2:45] • Einblick's progressive approximation engine [6:43] • How no-code tools impact productivity [17:18] • The critical steps to become more data-driven as an organization [24:30] • How research universities like MIT support high-risk, long-term research [38:37] • How ML applied to databases enables them to be faster and more efficient [42:03] • How real-time collaboration environments like Google Docs are likely to become more widespread for data science tasks [ 49:24] Additional materials: www.superdatascience.com/571

In this episode, Jon is back with another A.I. model breakthrough! He updates listeners on OpenAI's outstanding DALL-E 2 model. The new natural language processing model churns out staggering visual examples of whatever text your mind can dream up. Additional materials: www.superdatascience.com/570

Research Scientist at Meta AI, Dr. Noam Brown, joins Jon Krohn to discuss his award-winning no-limit poker-playing algorithms and the real-world implications of his game-playing A.I. breakthroughs. In this episode you will learn: • What Meta A.I. is and how it fits into Meta, the company [3:01] • Noam's award-winning no-limit poker-playing algorithms, Libratus and Pluribus algorithms. [4:33] • What game theory is and how does Noam integrate it into his models? [8:45] • The real-world implications of Noam’s game-playing A.I. breakthroughs [25:24] • Why Noam elected to become a researcher at a big tech firm instead of in academia [27:06] • The main barriers to getting AI game theory techniques beyond games to self-driving cars [30:16] • Recommendations for people who want to break into poker AI [37:45] Additional materials: www.superdatascience.com/569

In this episode, Jon updates listeners on one of the industry's biggest breakthroughs to date –Google's new natural language processing model, PaLM. The key innovation with PaLM is scaling up Google's Pathways modeling approach to half a trillion parameters — many-fold more parameters than had previously been trained using this approach. Additional materials: www.superdatascience.com/568

In this episode, the MIT Press Director and Publisher, Dr. Amy Brand, joins Jon Krohn to discuss open-access publishing in data science and how to address the inequalities that exist for women and minorities in STEM. In this episode you will learn: • What it’s like to run the prestigious MIT Press [4:34] • How open access makes scholarly work more impactful [6:34] • How publishing outstanding STEM books for broader audiences, including for children, can help address STEM biases [19:28] • Amy's award-winning documentary Picture A Scientist [25:28] • What it's like to executive produce a documentary [37:24] • What can be done to change STEM to make it more welcoming to minorities [48:44] • The best open-source model going forward [58:26] • What fascinates Amy about natural language processing [1:01:30] • How author metadata in standardized taxonomies can help authors receive the credit they deserve [1:04:50] Additional materials: www.superdatascience.com/567

In this episode, Jon reflects on the Chinese proverb: "The best time to plant a tree was 20 years ago. The second best time is now." He also challenges listeners to reflect on their long-term goals that have gone unfulfilled. Additional materials: www.superdatascience.com/566

In this episode, Jeremie Harris dives into the stirring topic of AI Safety and the existential risks that Artificial General Intelligence poses to humankind. In this episode you will learn: • Why mentorship is crucial in a data science career development [15:45] • Canadian vs American start-up ecosystems [24:18] • What is Artificial General Intelligence (AGI)? [38:50] • How Artificial Superintelligence could destroy the world [1:04:00] • How AGI could prove to be a panacea for humankind and life on the planet. [1:27:31] • How to become an AI safety expert [1:30:07] • Jeremie's day-to-day work life at Mercurius [1:35:39] Additional materials: www.superdatascience.com/565

In this episode, Jon speaks with the CEO of Hugging Face, Clem Delangue, about open-source machine learning and transformer architectures, while attending the ScaleUp:AI Conference in New York. Additional materials: www.superdatascience.com/564

In this episode, superstar data science YouTuber Tina Huang joins us to discuss what it's like to work at one of the world's largest tech companies, her strategies for efficient learning, and how best to prepare for a career in data science from scratch. In this episode you will learn: • The key areas to focus on when getting started in data science [6:01] • Tina’s five steps to consistently doing anything [11:55] • Tina's day-to-day life as a data scientist at one of the world’s largest tech companies [20:02] • How Tina's computer science background helps her work [26:20] • Traditional banking culture vs big tech [32:12] • How Tina's background in pharmacology impacts her work in data science [36:15] • The software languages that Tina uses daily in her work [45:30] • How Tina’s SQL course practically prepares you for data science interviews [47:24] Additional materials: www.superdatascience.com/563

In this episode, Jon shares his daily technical exercise, which is part of an extensive habit tracking system that allows him to achieve more, create more structure within his day, and cut out bad habits. By completing mathematics, computer science, or programming exercise daily, Jon is able to hone his technical skills in a limitlessly broad field and open new professional opportunities in the long run. Additional materials: www.superdatascience.com/562

In this episode, Ribbon Health CTO Nate Fox joins us to discuss the ins and outs of APIs. Tune in to hear him share how he and his team build out APIs from scratch; how they ensure the uptime and reliability of APIs and how they leverage machine learning to improve the quality of healthcare delivery and maximize their social impact. In this episode you will learn: • What are APIs? [13:20] • How Ribbon Health’s data API leverages ML models to improve the quality of healthcare delivery [16:08] • How to design a data API from scratch [20:00] • How to ensure the uptime and reliability of APIs [25:28] • How Ribbon uses knowledge graphs, manually labeled data samples, and an XGBoost model with hundreds of inputs to assign a confidence score [27:14] • Nate’s favorite tool for easily scaling up the impact of data science [37:40] • What is Nate’s day-to-day like? [34:34] • The qualities Nate looks for when hiring data scientists [39:50] • How scientists and engineers can make a big social impact in health technology [42:50] Additional materials: www.superdatascience.com/561

In this episode, Jon shares his daily habit of reading two pages and explains how it has transformed his productivity. Additional materials: www.superdatascience.com/560

Natural language processing expert and PhD student Melanie Subbiah sits down with Jon Krohn to discuss GPT-3, its strengths and weaknesses, and the future of NLP. In this episode you will learn: • What is GPT-3? [6:24] • The strengths and weaknesses of GPT-3 [14:38] • What is autoregression? [18:03] • GPT-3's new fine-tuning abilities [20:02] • Bias issues with GPT-3 [22:47] • The future of natural language processing models [27:54] • How Melanie ended up working at OpenAI [38:13] • Melanie’s self-study process [42:19] • Melanie's work on OpenAI API [45:45] • How to address the climate change and bias issues that cloud discussions of large natural language models [49:40] • Why Melanie chose to do a PhD at Columbia University [1:01:17] • The machine learning tools Melanie’s most excited about [1:08:09] Additional materials: www.superdatascience.com/559

In this episode, Jon shares the key topics he recently discussed with the Open Data Science Conference. From the approach behind his extensive machine learning and deep learning content library to revealing the key tools and software he uses daily, get to know Jon and his process a little better. Additional materials: www.superdatascience.com/558

Pandas expert Matt Harrison sits down with Jon Krohn to discuss tips, tricks and best practices for Pandas learning and mastery. In this episode you will learn: • Pros and cons of self-publishing and working with a publisher [5:05] • Matt's six tips for using Pandas [17:13] • The best way for corporate teams to level up their skills [40:04] • How to learn anything effectively [47:14] • Matt’s tricks for staying motivated [50:00] • Matt’s recommendations for using Git and the Unix command line [1:00:14] • Matt’s recommended software libraries for working with tabular data [1:19:45] Additional materials: www.superdatascience.com/557

Discover Jon’s extensive library of machine learning content and learn why Jon's Machine Learning House forms the knowledge structure of an outstanding data scientist or ML engineer. Additional materials: www.superdatascience.com/556

Data scientist and Youtuber Ken Jee joins Jon Krohn for a deep dive into the world of sports analytics and brings us behind the makings of his large, online data science community. In this episode you will learn: • The inspiration behind Ken’s YouTube videos [18:03] • Ken’s four steps for getting started in data science [24:18] • How sports analytics is transforming sports like golf [33:32] • Ken’s favorite tools for software scripting as well as for production code development [41:10] • How the #66DaysofData hashtag can supercharge your capacity as a data scientist [42:51] • Ken’s data science podcast Ken’s Nearest Neighbors [54:11] • LinkedIn Q&A [1:00:32] Additional materials: www.superdatascience.com/555

In this episode, Jon shares where you can find his extensive deep learning video content and courses. Tune in to learn more about his deep learning curriculum and where you can learn for free. Additional materials: www.superdatascience.com/554

In this episode, Dr. Josh Starmer, the creative, musical genius behind the wildly popular YouTube channel StatQuest joins the podcast to discuss statistics, learning and communication secrets, and how he grew his YouTube channel to over 650,000 subscribers. In this episode you will learn: • The inspiration behind Josh’s YouTube channel [18:39] • Josh's simple approach to learning something new [34:25] • Josh's secret tool for creating YouTube videos with over a million views [51:01] • The StatQuest Illustrated Guide to Machine Learning [53:34] • How and when Josh uses R vs. Python [1:07:53] • How to cluster any types of data using the R randomForest package [1:11:24] • Why Josh left his academic career [1:14:24] • The two stats concepts Josh thinks everyone should know [1:38:50] Additional materials: www.superdatascience.com/553

In this episode of Five-Minute Friday, Jon recaps the most popular SuperDataScience podcast episodes from 2021. See what you might have missed and catch up today! Additional materials: www.superdatascience.com/552

In this episode, gifted author and software engineer Wah Loon Keng joins the podcast to dive deep into reinforcement learning. From its history to limitations, modern industrial applications, and future developments– there's no better expert to learn from if you want to know more about this complex topic. In this episode you will learn: • What is reinforcement learning? [4:50] • Deep reinforcement learning vs reinforcement learning [13:17] • A timeline of reinforcement learning breakthroughs [16:17] • The limitations of deep RL today [39:53] • Deep RL applications [53:10] • Keng's open-source SLM-Lab framework [57:51] • Keng’s responsibilities as an AI engineer [1:02:17] • What is the future of RL? [1:08:05] Additional materials: www.superdatascience.com/551

Jon is back with another Five-Minute Friday habit-tracking episode! Listen in as he explains how writing morning pages has helped his data science work flourish with creativity. Inspired by Julia Cameron's book The Artist's Way, he details his morning pages routine and how it kickstarted a new chapter in his career. Additional materials: www.superdatascience.com/550

In this episode, Glean software engineer and Stanford graduate Lauren Zhu joins us to discuss her role at a fast-growing startup, working on natural language processing projects, and how she remains inspired by pursuing her side passions. In this episode you will learn: • Lauren's experience as a course assistant [5:53] • Stanford's Hacking the Coronavirus Course [11:53] • How do you empower minority groups in AI [19:45] • Lauren on zero-shot multilingual neural machine translation [23:25] • Lauren's work at Glean [27:58] • The Contrary Talent Network [34:30] • The tools Lauren uses at Glean [43:39] • The most important skills to possess as a data scientist [47:29] Additional materials: www.superdatascience.com/549

Our Five-Minute Friday series on habit tracking returns with a look at one of Jon's daily mindfulness habits–meditation. Learn how to keep this habit going for the long run and discover which tools help Jon stay on track. Additional materials: www.superdatascience.com/548

In this episode, Dr. Jonathan Flint, Professor of Psychiatry and Biobehavioral Sciences at the University of California Los Angeles, joins us to discuss how he uses data science and machine learning to explore the link between genetics and depression. In this episode you will learn: • Johnathan's background [2:53] • How we know that genetics plays a role in complex human behaviors including psychiatric disorders like anxiety, depression, and schizophrenia [8:00] • The role that data science and ML play in modern genetics research [15:08] • About Jonathan book "How Genes Influence Behavior" [19:45] • The day-to-day life of a world-class medical sciences researcher [32:24] • The open-source software libraries that Jonathan uses for data modeling [40:33] • A single question you can ask to prevent a severely depressed person from committing suicide [52:00] • LinkedIn Q&A [54:41] • The future of psychiatric treatments [1:05:35] Additional materials: www.superdatascience.com/547

Our Five-Minute Friday habit-tracking series continues! Learn more about alternate-nostril breathing–the mindfulness technique that is scientifically proven to lower blood pressure and regulate the stress response. Additional materials: www.superdatascience.com/546

Data scientist and entrepreneur Matthew Russell joins Jon Krohn to discuss the intersection of machine learning and fitness and dive deep into the strategies he and his team at Strongest AI use to scale data-intensive real-time applications. In this episode you will learn: • About Strongest's event platform and iOS app [6:06] • How Strongest scaled to serve million [8:14] • Strongest's unique approach to building a fitness app [17:50] • How to rapidly test ML models for deployment [29:01] • The three critical traits Matthew looks for in anyone he hires [33:11] • Mining the Social Web [41:14] • The values instilled in Matthew by pursuing a military education [53:30] • The key skills Matthew wishes he’d learned earlier in his career [1:03:51] Additional materials: www.superdatascience.com/545

Our habit-tracking series continues with a look at how making your bed can jumpstart your mornings, prevent you from taking part in negative habits and help you become happier. Additional materials: www.superdatascience.com/544

Nicole Büttner (Founder and CEO of Merantix Labs) joins the podcast to discuss driving A.I. innovation, automation, and transformation and building the ideal A.I. start-up founding team. In this episode you will learn: • The three factors that spark A.I. innovation [12:48] • How to make great use of the unlabelled, unbalanced data sets [18:54] • How to engineer reusable data and software components [25:09] • Merantix's A.I. Canvas framework for successful innovation [29:59] • How to be a part of Merantix's program as a founder [45:23] Additional materials: www.superdatascience.com/543

Revisit the much-underrated continuous calendar and get started with this uncommon planning method thanks to Jon's 2022 template. Additional materials: www.superdatascience.com/542

In this episode, Kevin Hu joins the podcast to talk about founding and growing the data observability startup, Metaplane. Listen in to hear about his time in academia at MIT, his experience with Y Combinator, and his current routine as a technical founder. In this episode you will learn: • What is data observability? [4:35] • How to identify data quality issues? [8:56] • Kevin's PhD research on automating data science systems using machine learning [16:18] • Why Kevin launched Metaplane [28:50] • The pros and cons of an academic career relative to the start-up hustle [31:57] • Kevin's experience in Y-Combinator accelerator [39:50] • The software tools he uses daily as a CEO [50:54] • What Kevin looks for in data engineer hires [56:13] Additional materials: www.superdatascience.com/541

In this episode, Jon opens up about starting his day with a glass of water – his first morning habit that sets his day off on a healthy and successful note. Additional materials: www.superdatascience.com/540

In this episode, Serg Masís joins the podcast to share his in-depth technical knowledge of Interpretable Machine Learning. Together they discuss why this field matters, how it’s evolving, and so much more. In this episode you will learn: • What is interpretable machine learning? [8:41] • The social and financial ramifications of interpreting models incorrectly [10:23] • The challenges involved in interpretable ML [16:00] • The most important interpretable ML concepts to master [19:54] • The future of Interpretable ML [32:41] • What it’s like to be a Climate & Agronomic Data Scientist [42:28] • Serg’s day-to-day tools [49:05] • Serg's productivity tips [50:25] • Why Serg pursued a Master's in Data Science [52:25] Additional materials: www.superdatascience.com/539

In this episode, Jon shares his "life-changing" habit tracking system that has allowed him to achieve more, create more structure within his day and cut out bad habits. Additional materials: www.superdatascience.com/538

Sadie St. Lawrence returns to discuss the biggest data science trends that are set to take over the industry in 2022. In this episode you will learn: • A look back at data science trends for 2021 [4:03] • Micro and macro data science trends for 2022 [12:30] • AutoML tools [15:20] • The social implications of deepfakes [21:21] • Scalable AI [38:40] • Macro data science trends for 2022 [42:45] • The impact of the remote-working economy in data science [43:21] • Blockchain in data science [50:28] • Data literacy of the global workforce [1:01:07] Additional materials: www.superdatascience.com/537

Jon goes over his five biggest learnings from 2021 and what he hopes to work on in 2022. Additional materials: www.superdatascience.com/536

Prolific data science entrepreneur and Y Combinator alum Austin Ogilvie (Laika, Yhat) joins Jon Krohn for a revealing look into his journey of starting, growing, and selling a data science startup. From liberal arts graduate to twice successful technical founder, take a seat and learn from the best. In this episode you will learn: • The story behind the naming of Yhat and its early beginnings [5:10] • Austin and Yhat's experience at Y Combinator [19:00] • The benefits of being a technical founder [25:00] • From arts degree graduate to successful tech entrepreneur [27:00] • Austin's latest venture, Laika [39:30] • The tools that Austin uses day-to-day [47:30] • Unity gaming environment [49:58] • What makes a great data scientist [56:23] Additional materials: www.superdatascience.com/535

Jon sends a holiday greeting to all listeners. Additional materials: www.superdatascience.com/534

Dr. Brett Tully joins us on the podcast to discuss his work as Director of AI Output Systems at Nearmap and his previous research in biomedical topics and nuclear fusion. In this episode you will learn: • What is Nearmap? [5:22] • What is a Director of AI Output Systems? [7:51] • A case study [20:35] • MLOps at Nearmap [26:37] • Brett’s day-to-day and what he looks for in hires [40:19] • Brett’s academic and research history [53:30] • Brett’s work in nuclear fusion and predictions for the technology [1:04:48] • The tools Brett used in his research [1:26:34] • ProCan project [1:34:27] • Brett’s prediction for future AI applications [1:48:30] Additional materials: www.superdatascience.com/533

Jon discusses one helpful framework when it comes to problem-solving and how data scientists are uniquely positioned to employ this technique. Additional materials: www.superdatascience.com/532

Jeroen Janssens joins on the podcast to discuss his book on utilizing the command line for data science and the importance of polyglot data science work. In this episode you will learn: • The genesis of Jeroen’s book [3:24] • Data Science at the Command Line [8:55] • Creating your own command line tools [22:07] • Polyglot data scientist [24:29] • Data Science Workshops [27:01] • Jeroen’s PhD research [30:38] Additional materials: www.superdatascience.com/531

Jon details his top ten AI thought leaders hoping that his suggestions prove valuable to you in your data science journey. Additional materials: www.superdatascience.com/530

Dave Niewinski joins us to discuss his prolific work in robotics both as a consultant and a popular YouTuber. In this episode you will learn: • Dave’s Armoury [4:44] • Robotic cornhole tournament [12:33] • Dave’s many robots [14:25] • Dave’s idea process [28:51] • Future robots [31:43] • Dave’s consulting business [33:27] • Tools Dave likes to use [37:05] • How did Dave get started in this line of work? [38:50] • Dave’s advice to people who want to get into robotics [41:18] • What is Dave excited about in the future? [45:38] Additional materials: www.superdatascience.com/529

Jon explores his personal anxieties as a content creator to encourage fellow creators to keep sharing their knowledge. Additional materials: www.superdatascience.com/528

Peter Bailis joins the podcast to discuss the work of his company that solves complex commercial problems through automated data analysis. In this episode you will learn: • Meaning of the name Sisu [3:08] • What Sisu does [4:45] • Sisu and the data science stack [17:00] • Going from academia to startups [22:37] • What Sisu looks for when hiring [28:57] • Peter’s favorite tools [32:40] • Peter’s academic research [45:02] Additional materials: www.superdatascience.com/527

I finish up our three-part series on the results of the O’Reilly Survey, looking at the highest-paying data frameworks. Additional materials: www.superdatascience.com/526

Karen Jean-Francois joins us to discuss how she wants to empower her team members and a wider audience of data scientists battling imposter syndrome. In this episode you will learn: • Karen’s background as a hurdler [4:42] • Women in Data Podcast [10:32] • Cardlytics [19:04] • Karen’s background and current career [22:55] • Karen’s favorite tools [31:29] • Karen’s balance of fitness and work [34:45] • The biggest challenge of Karen’s career [47:09] • Advancement in data [54:13] • What is Karen most excited about? [59:40] Additional materials: www.superdatascience.com/525

In this episode, I go over the highest-paying data tools based on the O’Reilly survey. Additional materials: www.superdatascience.com/524

Wes McKinney joins us to discuss the history and philosophy of pandas and Apache Arrow as well as his continued work in open source tools. In this episode you will learn: • History of pandas [7:29] • The trends of R and Python [23:33] • Python for Data Analysis [25:58] • pandas updates and community [30:10] • Apache Arrow [41:50] • Voltron Data [55:10] • Origin of Wes’s project names [1:08:14] • Wes’s favorite tools [1:09:46] • Audience Q&A [1:15:34] Additional materials: www.superdatascience.com/523

I provide you with some quick definitions of data tools vs data platforms to prep us for deep dives in future episodes. Additional materials: www.superdatascience.com/522

Khuyen Tran joins us to discuss her work as a prolific technical writer and undergraduate data science student. In this episode you will learn: • Khuyen’s online writing [4:00] • Book writing [8:50] • How you can increase your engagement [13:49] • Khuyen’s work with Towards Data Science and NVIDIA [19:01] • Ocelot Consulting [24:08] • Khuyen’s undergrad work [32:12] • Audience questions [47:00] Additional materials: www.superdatascience.com/521

I take a look at the results of O’Reilly’s survey on salaries for data scientists in 2021. Additional materials: www.superdatascience.com/520

James Hodson joins us to discuss his philosophy and work at A.I. For Good and how they aim to promote sustainability and A.I. use for social issues. In this episode you will learn: • AI for Good [5:17] • Founding of AI for Good [8:50] • Case studies [14:58] • How you can get involved [46:29] • Skills James looks for in hires [50:39] Additional materials: www.superdatascience.com/519

This week, I provide a short but important bit of advice on failure. Additional materials: www.superdatascience.com/518

Sadie St. Lawrence talks in-depth about her extensive work as a data science educator through both online and collegiate courses as well as her organization for diversifying data science careers. In this episode you will learn: • Sadie’s education work in SQL [4:13] • The popularity of Sadie’s course [13:32] • Sadie’s forthcoming machine learning certificate course [16:29] • Women in Data [25:32] • Sadie’s non-technical background [36:17] • NFTs and VR [46:41] Additional materials: www.superdatascience.com/517

In this episode, I finish up my saga into the effects of caffeine on productivity. Additional materials: www.superdatascience.com/516

Chrys Wu joins us to discuss her community organizations, her tips, and her recommended resources for building data science communities for impact. In this episode you will learn: • The world of K-Pop [ 4:07] • Chrys’s talk at the R Conference [8:56] • Write/Speak/Code [14:05] • Hacks/Hackers [21:58] • Tips on developing data communities [27:22] Additional materials: www.superdatascience.com/515

In this episode, I dive into the nuts and bolts of data on my experiment into caffeine and productivity. Additional materials: www.superdatascience.com/514

Denis Rothman joins us to discuss his writing work in natural language processing, explainable AI, and more! In this episode you will learn: • What are transformers and their applications? [7:54] • Denis’s book on explainable AI [25:08] • AI by Example [35:53] • LinkedIn audience questions [42:00] Additional materials: www.superdatascience.com/513

I dive into a personal experiment to test my productivity relative to my coffee intake and if caffeine is actually hurting my productivity. Additional materials: www.superdatascience.com/512

Drew Conway joins us on the first live podcast to discuss his work in private investing and how data science figures into and improves his work. In this episode you will learn: • The R Conference and NYHackR [6:33] • Machine Learning for Hackers [20:17] • Two Sigma and Drew’s work [28:27] • Drew’s team structure at Two Sigma [35:12] • Audience Q&A [46:27] Additional materials: www.superdatascience.com/511

In this episode, I dive into the world of reinforcement learning and deep reinforcement learning and the benefits of both. Additional materials: www.superdatascience.com/510

Parinaz Sobhani joins us to discuss the cutting-edge work of Georgian, a collaborative company that helps start-ups implement and scale machine learning and AI. In this episode you will learn: • Parinaz’s work at Georgian [5:35] • Use cases of Georgian’s work [14:35] • Tools and approaches Parinaz uses [32:27] • Environmental concerns of machine learning [42:52] • Hiring at Georgian and what Parinaz looks for [48:18] • How did Parinaz become interested in this? [56:19] • Fairness in AI [1:09:01] Additional materials: www.superdatascience.com/509

In this episode, I discuss an interesting bit of my grandmother’s view about the process of working and going through life. Additional materials: www.superdatascience.com/508

Rob Trangucci joins us to discuss his work and study in Bayesian statistics and how he applies it to real-world problems. In this episode you will learn: • Getting Rob on the show [8:12] • Stan [9:34] • Gradients [18:15] • What is Bayesian statistics? [23:05] • Multi-modal deep learning [45:20] • Stan package [53:46] • Applications of Bayesian stats [1:09:47] • The day-to-day of a PhD in stats [1:21:56] • What does the future hold? [1:42:37] Additional materials: www.superdatascience.com/507

In this episode, I continue with last week’s theme and discuss the differences between supervised and unsupervised learning. Additional materials: www.superdatascience.com/506

Hadelin de Ponteves joins us to discuss his latest educational work and how his skills as a data science educator helped him start his career in acting. In this episode you will learn: • What has Hadelin been up to? [4:27] • Hadelin’s cinema career and data science crossover [16:02] • Sleep for productivity [27:27] • How did Hadelin decide to undertake this? [32:26] • Bollywood vs Hollywood [37:26] Additional materials: www.superdatascience.com/505

In this episode, I give a quick introduction to subcategories of supervised learning problems. Additional materials: www.superdatascience.com/504

Pieter Abbeel joins us to discuss his work as an academic and entrepreneur in the field of AI robotics and what the future of the industry holds. In this episode you will learn: • How does Pieter do it all? [5:45] • Pieter’s exciting areas of research [12:30] • Research application at Covariant [32:27] • Getting into AI robotics [42:18] • Traits of good AI robotics apprentices [49:38] • Valuable skills [56:40] • What Pieter hopes to look back on [1:04:30] • LinkedIn Q&A [1:06:51] Additional materials: www.superdatascience.com/503

In this episode, I explore a common issue plaguing people across fields: imposter syndrome. Additional materials: www.superdatascience.com/502

Jared Lander joins us to discuss his work as an R meetup organizer, the upcoming virtual R Conference, and his work as a consultant for a variety of companies from metal workers to professional football teams. In this episode you will learn: • Jared’s R meetups and our professional history [3:27] • NYHackR [6:42] • The R Conference [13:25] • R for Everyone [18:55] • Lander Analytics [22:10] • Job openings at Lander Analytics [25:04] • R vs. Python [29:15] • The importance of pizza in Jared’s life [32:19] Additional materials: www.superdatascience.com/501

Barr Moses joins us to discuss the importance of data reliability for pipelines and how companies can achieve data mesh. In this episode you will learn: • Data meshes [4:25] • Self-serve data reliability [15:36] • How Monte Carlo helps data up time [21:13] • How to build an effective data science team [26:50] • LinkedIn Q&A [31:50] Additional materials: www.superdatascience.com/499

In this very special episode, we delve into a live yoga Nidra practice with Jes Allen and go over how you can open up to consciousness through yoga practice. In this episode you will learn: • [3:40] What Yoga means • [10:00] Jes’s current work as a yoga practitioner • [22:31] How to find Jes online • [27:09] The Yoga Nidra practice • [54:50] Coming out of the practice Additional materials: www.superdatascience.com/500

In this episode, I dive into a reoccurring pattern I’ve noticed where beginners, myself included, think they’re more skilled and experienced than they really are. Additional materials: www.superdatascience.com/498

Benjamin Todd joins us to discuss his work helping professionals maximize their career capital, the top skills to learn across professions, and more. In this episode you will learn: • How Benjamin helped me become a data scientist [6:56] • How did 80,000 Hours come about? [9:39] • The impact of 80,000 Hours [14:46] • Funding [17:23] • Where does the name come from? [23:32] • What kind of advice does Benjamin give to people? [25:21] • How data scientists can make an impact [42:04] • How can someone strategize about their career? [1:02:53] • Top skills that everyone should learn [1:05:49] Additional materials: www.superdatascience.com/497

In this episode, you’ll enjoy a fictional narrative I’ve titled “2040: A Brain-Computer Interface Story”. Additional materials: www.superdatascience.com/496

Greg Coquillo joins us to discuss his work on ROI for startups and the best ways to make the most of your company’s AI investment. In this episode you will learn: • Our connection through Harpreet’s happy hours and DSGO [4:48] • Greg’s content on LinkedIn [6:40] • The scope of Greg’s work [9:25] • Making the most out of AI [16:05] • LinkedIn Q&A [20:00] • Quantum machine learning [32:06] Additional materials: www.superdatascience.com/495

In this episode, I talk about an interesting thought experiment that helps you appreciate your existence. Additional materials: www.superdatascience.com/494

Anjali Shrivastava joins us to discuss her data science degree and her content creation efforts to bring data science to the people. In this episode you will learn: • Anjali’s studies [2:00] • Anjali’s YouTube channel [11:57] • The content creation process [17:58] • Yoga during the pandemic [21:34] • Anjali as a writer [24:38] • Anjali’s dual degrees [31:28] • Anjali’s previous data science roles [43:04] • Anjali’s first full-time data job [51:12] • Anjali’s hopes for the future [55:29] Additional materials: www.superdatascience.com/493

In this episode, I discuss the changing child mortality rate as evidence of how much better the world is and how much better it could be. Additional materials: www.superdatascience.com/492

Veerle van Leemput joins us to make the case for why you should be using R for production. In this episode you will learn: • Our shared powerlifting passion [2:47] • The stigma of using R [12:02] • What does Analytic Health do? [13:55] • How Analytic Health uses R [19:08] • Tidyverse [34:44] • Tools for API creation [37:09] Additional materials: www.superdatascience.com/491

In this episode, I discuss why you should avoid the visually pleasing but flawed pie chart. Additional materials: www.superdatascience.com/490

Vin Vashishta joins us to discuss his AI consulting work and his philosophy on AI strategy for monetization. In this episode you will learn: • V-Squared [4:59] • Vin’s online content [17:18] • Low-code/no-code in data science [25:33] • Top five gap skills [35:19] • Data sets for insights on consumers and targeting [40:26] • Are there socially beneficial data science and machine learning applications? [43:16] • The most difficult data science problem Vin ever faced [50:39] Additional materials: www.superdatascience.com/489

In this episode, I discuss the simple and cheap ways you can buy yourself more time during the day. Additional materials: www.superdatascience.com/488

Susan Walsh joins us to discuss the importance of data cleaning and normalization and how clean procurement data can save companies money. In this episode you will learn: • Susan’s “COAT” system [7:16] • The Classification Guru [15:39] • Case studies [22:46] • Susan’s book [30:26] Additional materials: www.superdatascience.com/487

In this episode, I go over the world history of calculus and how we still use these techniques today. Additional materials: www.superdatascience.com/486

Doug Eisenstein joins us for a great and in-depth conversation on data engineering in the financial sector. In this episode you will learn: • The founding of Advanti [4:37] • Aristos and solution products [16:45] • The kinds of financial industries and how Doug helps [26:25] • Entity Extraction [34:27] • Temporality data [44:27] • How to work with Doug [58:19] Additional materials: www.superdatascience.com/485

In this episode, I discuss interesting research on why humans are so quick to lose faith in algorithms. Additional materials: www.superdatascience.com/484

Andrew Jones joins us to discuss data science interviews and how you can maximize your chances on interview time, resume, and more! In this episode you will learn: • Data Science Infinity [5:40] • “The Essential AI and Data Science Handbook for Recruitment” [17:40] • How can aspiring data scientists set themselves apart? [21:30] • What skillset should data scientists have? [34:36] • Should data science be trying to be data engineers? [41:14] • How can organizations ensure data science projects are a success? [50:50] Additional materials: www.superdatascience.com/483

In this episode, I talk about the advantages of using a continuous calendar. Additional materials: www.superdatascience.com/482

Kris Tait joins us to discuss the vast world of digital performance marketing and how automation, data, and optimization play an important role. In this episode you will learn: • What is performance marketing? [3:29] • How can advertisers take advantage of these tactics? [13:04] • The importance of quality data in performance marketing [20:19] • Human value performance marketing [25:30] • How does Croud optimize? [29:05] • What are the best KPIs in this industry? [34:02] • Roles available at Croud now [39:11] • Typical tools at Croud [42:43] • What clients work best for Croud? [48:56] Additional materials: www.superdatascience.com/481

In this episode, I go over my top 5 tips for refining your perfect data science resume. Additional materials: www.superdatascience.com/480

Maureen Teyssier joins us to discuss the cutting-edge work Reonomy is doing in commercial property real estate and her views and tips on building a great data science team. In this episode you will learn: • Maureen’s work with Reonomy [5:40] • Knowledge graphs and use cases [7:35] • Other tools Reonomy uses [18:58] • What Maureen looks for in potential hires, soft skills and hard skills [26:28] • Hiring at Reonomy [41:40] • Maureen’s tips for growing a data science team [48:55] • Tools to transition from academia to industry [52:45] Additional materials: www.superdatascience.com/479

In this episode, I go over my 5 keys to success to tackle any goal. Additional materials: www.superdatascience.com/478

Sidney Arcidiacono joins us to discuss her studies and work at Make School and her interest in utilizing AI for healthcare, as well as her tips and strategies for becoming a successful early-career data scientist. In this episode you will learn: • What is Make School? [5:00] • Sidney’s interest in AI and computer science [10:56] • Graph theory and graph convolutional neural networks [19:53] • What tools does Sidney use for her work? [31:16] • Sidney’s internship [36:52] • How other beginners can get involved in data science [38:12] • Sidney’s goals [41:57] Additional materials: www.superdatascience.com/477

In this episode, I discuss the amazing benefits of implementing peer-driven learning in your professional life. Additional materials: www.superdatascience.com/476

David Langer joins us to discuss his work as a data analytics educator and his beliefs in the use of Excel, SQL and R in analytics work. In this episode you will learn: • Intro to Dave on Data [6:50] • 20% analytics that drives 80% of ROI [11:04] • The benefits of SQL [19:15] • The uses of R [24:50] • Machine learning [34:15] Additional materials: www.superdatascience.com/475

In this episode, I discuss the architecture of a “machine learning house”, representing the skills and learnings you can use as foundations to build your data science career. Additional materials: www.superdatascience.com/474

Anima Anandkumar joins us to discuss her work as a researcher in machine learning at NVIDIA and a professor at CalTech, and how they often go hand-in-hand and inform each other. In this episode you will learn: • Anima’s recent discovery of yoga [5:20] • How does Anima balance her work? [12:25] • Applications of Anima’s work [14:45] • Tensors [22:55] • Anima’s favorite NVIDIA projects [35:35] • What tools does NVIDIA use? [41:55] • CalTech interdisciplinary science [47:41] • The path to generalized artificial intelligence [57:19] • The skills to have to get into this field [1:00:27] • LinkedIn questions for Anima [1:07:03] Additional materials: www.superdatascience.com/473

In this episode, I share a note I received from a student who expressed his thoughts on the learning that never stops as he goes through his data science career. Additional materials: www.superdatascience.com/472

Kirill Eremenko returns to the SDS podcast as a guest to debunk common myths you may believe about getting a data science job. In this episode you will learn: • What has Kirill been up to? [3:48] • The genesis of the 99-days challenge [5:27] • 5 myths about pursuing a data science career [15:49] • First data science jobs [1:00:53] • 5 components for success [1:08:19] Additional materials: www.superdatascience.com/471

In this episode, I follow up on the popular book recommendation portion of the podcast with my own list of favorite books. Additional materials: www.superdatascience.com/470

Konrad Körding joins us to discuss his work in educating the next generation in deep learning and his views on the importance of causality in deep learning research. In this episode you will learn: • Konrad’s academic background [3:54] • Neuromatch Academy [5:23] • Artificial general intelligence [35:02] • Defining deep learning [41:24] • Symbol representation [44:12] • Konrad’s career journey [47:25] • What other skills should you develop for the future? [52:46] • What is the future of intelligence in our timeline? [56:37] Additional materials: www.superdatascience.com/469

In this episode, I tackle another historical topic: the history of data. Additional materials: www.superdatascience.com/468

Noah Gift joins us to discuss how he believes data science urgency and the end of hierarchies will change the world for the better. In this episode you will learn: • Catch up with Noah [2:50] • Educational options to pursue in data science [13:09] • Outside university education [24:06] • Noah as a prolific author [28:15] • Urgent applications of technology [37:34] • Noah’s income streams color code [48:38] • How to harness our free time to solve big problems [54:13] • Noah’s Coursera course [1:09:12] Additional materials: www.superdatascience.com/467

In this episode, I go over what separates a good data scientist from a great one in skills, practices, and approach. Additional materials: www.superdatascience.com/466

Konrad Kopczynski joins us to discuss how data, tracking, analytics, and key performance indicators can help your professional and personal development. In this episode you will learn: • What does Konrad do [3:40] • Tools and techniques used in Impakt Advisors [10:35] • Impakt’s unique hiring model [18:53] • How does Impakt manage remote work [21:36] • Konrad’s professional history and daily structure [28:42] • Konrad’s Iron Man triathlon [44:11] • Konrad’s years’ long project on presidential biographies [47:46] Additional materials: www.superdatascience.com/465

In this episode, I tackle three often conflated terms - AI, machine learning, and deep learning - to shine some light on what exactly they are. Additional materials: www.superdatascience.com/464

Matt Dancho joins us to discuss his various packages for time series analysis and his courses on the topic through his company Business Science. In this episode you will learn: • How Matt got into time series library development [4:22] • Business Science [7:00] • R Shiny [9:36] • Matt’s 6 time series models [14:11] • Timetk [15:02] • Modeltime [29:32] • Gluon package [36:04] • Modeltime Ensemble [43:12] • Modeltime H2O [45:22] • Modeltime Resample [48:10] Additional materials: www.superdatascience.com/463

In this episode, I discuss taking a positive approach to the good things that happen in life, rather than focusing on potential negative outcomes. Additional materials: www.superdatascience.com/462

Sam Hinton joins us to discuss his work since assisting COVID-19 data pipelines, now working in renewable energy and applications of ML and MLOps for the industry. In this episode you will learn: • Catching up with Sam [3:05] • Updates on the COVID-19 data pipelines [7:07] • Sam’s current work at Arenko [10:41] • Sam’s stint on Survivor, PhD, and his software engineering background [16:32] • Machine learning in renewable energy [35:23] • Sam’s day-to-day tools [49:33] • How can listeners utilize MLOps [53:08] • Sam’s forthcoming novel [59:05] Additional materials: www.superdatascience.com/461

In this episode, I talk about the ancient history of algebra, an important component of data science today. Additional materials: www.superdatascience.com/460

Vince Petaccio joins us to discuss how he sees data science, ML, and AI making positive impacts in the fight against climate change. In this episode you will learn: • Where in the world is Vince? [2:08] • Vince’s interest in climate science [4:33] • The Citizen’s Climate Lobby [9:12] • Where data science comes in [13:28] • Risks of relying on tools [31:54] • How can you make an impact? [37:28] Additional materials: www.superdatascience.com/459

In this week’s episode, I take you behind the scenes of our video tutorial productions to see what goes into making our tutorials. Additional materials: www.superdatascience.com/458

Harpreet Sahota joins us to discuss his data science mentorship work outside his day job and how you can land your dream job. In this episode you will learn: • Harpreet’s current life and location [2:25] • Data Community Content Creator Awards [8:37] • The Artists of Data Science Podcast [14:46] • Data Science Dream Job [24:18] • Harpreet’s day job at Price Industries [30:48] • Coming in data science from a non-data background [40:55] • Tools and skills to know [47:57] Additional materials: www.superdatascience.com/457

In this week’s episode, I talk about one of my favorite time management techniques: the Pomodoro technique. Additional materials: www.superdatascience.com/456

Horace Wu joins us to discuss his work on Syntheia, a unique product that helps sift through massive amounts of legal data to augment the capacities and function of law firms. In this episode you will learn: • Horace’s life and work in New York City [5:00] • Syntheia and Horace’s role there [6:25] • Horace’s background [12:07] • Nearmap [16:35] • Syntheia NLP use cases [21:46] • Design, coding, and the team [34:19] • What skills does one need for this field? [41:41] • What would Horace do differently and what is he excited for? [46:15] Additional materials: www.superdatascience.com/455

In this episode, I continue my discussion about the quick-paced growth of technology and how it impacts different fields. Additional materials: www.superdatascience.com/454

Stephen Welch joins to go over his year-end 2020 list of 10 important questions and pain points that machine learning can improve. In this episode you will learn: • Welch Labs on YouTube [4:54] • What Stephen’s been up to [7:56] • Stephen’s 2020 year-end blog post [10:11] • Stephen’s reflections on 10 areas worth focusing on [16:25] Additional materials: www.superdatascience.com/453

In this week’s episode, I discuss how technology propelled the recruitment industry forward and continues to do so today. Additional materials: www.superdatascience.com/452

Dan Shiebler joins us to discuss his category theory Ph.D. program, his full-time job at Twitter, and how the two crossover and combine in his overall data work. In this episode you will learn: • Dan’s neuroscience undergrad and MATLAB [4:12] • Dan’s Ph.D. timeline and research [14:01] • How to start a Ph.D. while working full time [22:45] • Dan’s work at TrueMotion and label data [30:39] • Dan’s title and role at Twitter [39:15] • Specific projects at Twitter [44:09] • What skills someone should bring to a Twitter job interview [52:06] • What machine learning approaches will be important in the future? [1:00:38] Additional materials: www.superdatascience.com/451

This week, Jon talks with Steve Fazzari about the physical and emotional benefits of practicing Yoga Nidra. Additional materials: www.superdatascience.com/450

Ayodele Odubela joins us to discuss fairness in AI and how we can work towards a more equitable and transparent world of data science and machine learning. In this episode you will learn: • Comet ML [3:22] • What is a data science evangelist? [7:08] • FullyConnected [12:04] • Imposter Syndrome and Ayodele’s book [15:57] • What Ayodele wished she learned from grad school [20:25] • Uncovering Bias in Machine Learning [27:00] • Where can we affect this positive change in fairness? [31:08] • The potential for a rosy future [49:20] • Ayodele’s LinkedIn Learning course [52:24] Additional materials: www.superdatascience.com/449

This week, I answer your questions about how to take yourself from data science practitioner to data science leader. Additional materials: www.superdatascience.com/448

Michael Segala joins us to discuss how machine learning can provide creative and novel solutions to longstanding problems in both the private and public sectors. In this episode you will learn: • SFL Scientific [4:20] • SFL’s example work [10:55] • Public sector vs private sector work [20:28] • Michael’s day-to-day [30:18] • What is Michael looking for in the people he hires? [33:38] • Michael’s career journey [41:39] • What is Michael excited about for the future? [48:38] Additional materials: www.superdatascience.com/447

This week I answer your questions about machine learning and how to educate yourself further in the field. Additional materials: www.superdatascience.com/446

Sinan Ozdemir joins us to share his work in conversational AI and what it takes to keep chatbots up to date and functional in an ever-changing world. In this episode you will learn: • Kylie.ai under Directly [4:51] • Sinan’s day-to-day work and tools [10:45] • Use cases [18:27] • AutoML’s role in these processes [21:55] • What hard or soft skills are needed for this work? [29:32] • Sinan’s background in teaching [34:58] • Sinan’s history in pure math and applied math [39:44] • Sinan’s math tattoos [43:48] Additional materials: www.superdatascience.com/445

In today’s episode, I answer your questions on how to best future-proof your data science career in AI, AutoML, and model interpretability. Additional materials: www.superdatascience.com/444

Jeff Wald joins us to discuss his book and the research he has done into the data and trends around the job market, the decline of the 9-5 office job, and more. In this episode you will learn: • The Birthday Rules [3:51] • A history of work [7:41] • The myth of the lifetime contract [12:15] • What the data says about now [21:02] • On-demand labor market [25:34] • Remote work [32:09] • What role will automation play? [46:27] • Future of employment from the study lens [48:30] Additional materials: www.superdatascience.com/443

In today’s episode, I discuss how focusing on process and habit building can provide more for you and your professional progress than simply chasing a goal. Additional materials: www.superdatascience.com/442

Kate Strachnyi joins us to discuss her work in data visualization education from conferences to published books as well as her tips for visualization best practices. In this episode you will learn: • What does Kate do (from her children’s perspective) [1:56] • What kind of tools does Kate employ? [5:19] • Kate’s day-to-day [13:03] • DATAcated Conference [16:03] • How do you amass a big LinkedIn following? [20:39] • Kate’s four published books [29:55] • The guidelines to follow to succeed in this field [37:00] • What’s next for Kate? [41:24] Additional materials: www.superdatascience.com/441

In this episode, I continue my discussion on the leaps we’re making towards AGI, by looking at MuZero. Additional materials: www.superdatascience.com/440

Deblina Bhattacharjee joins us to talk about her amazing work in computer vision and give advice for getting into and excelling in the field. In this episode you will learn: • Deblina’s master’s program work [4:03] • Deblina’s computer vision research and Ph.D. [11:46] • Deblina’s drumming hobby [20:18] • The daily work [24:40] • What key skills do you need as a data scientist? [33:21] • How can a data scientist prepare for the future? [37:03] • How does Deblina tackle time management? [40:24] Additional materials: www.superdatascience.com/439

In this episode, I discuss DeepMind’s latest breakthrough towards AGI and the stepping stones that got them there. Additional materials: www.superdatascience.com/438

Claudia Perlich joins us to discuss her work at one of the world’s largest hedge funds and how she got to work there, as well as her history of winning data science competitions. In this episode you will learn: • Life and work during the pandemic [2:23] • Claudia’s history with horses and riding [8:28] • Claudia’s work at Two Sigma [12:00] • Claudia’s role on a daily basis [20:51] • Tools of the trade [30:27] • What Claudia looks for when hiring [36:37] • What skills do future hires need? [40:32] • Claudia’s history with data science competitions [48:22] • Why work in finance and at Two Sigma? [1:00:19] Additional materials: www.superdatascience.com/437

In this episode, I continue my discussion on daily mindfulness practice and how to form a growing habit in it. Additional materials: www.superdatascience.com/436

Erica Greene joins us to discuss her work as a machine learning manager at Etsy, how they tackle problem-solving, how they implement ML scaling, and more. In this episode you will learn: • Erica’s role at Etsy and problem solving between platforms [2:28] • Interesting failures Erica has navigated [25:40] • How does Erica’s team select problems to solve [33:07] • Engineering at scale [40:15] • What does Erica’s working day look like? [46:30] • Etsy is hiring [53:00] • Diversity in hiring [57:12] • Do data scientists need PhDs? [1:01:26] Additional materials: www.superdatascience.com/435

In this episode, I discuss my use of mindfulness and attention sharpening tools to boost my productivity throughout the day. Additional materials: www.superdatascience.com/434

Ben Taylor joins us for the fourth time to discuss the upcoming 2021 trends in the world of data science as well as the post-COVID world. In this episode you will learn: • Ben’s passion for AI [9:41] • Delivering results and KPIs [12:43] • DataRobot and AutoML [20:38] • Transparent storytelling [24:29] • Federated learning [31:37] • ML productionization [37:01] • AI ethics [46:01] • Emerging software packages/tools [54:39] • Remote work [1:02:44] Additional materials: www.superdatascience.com/433

In this episode, I introduce myself, Jon Krohn, as the new host of the SuperDataScience podcast and give you a taste of what to look forward to in 2021! Additional materials: www.superdatascience.com/432

In this final episode featuring Kirill as the host, he examines and presents his top 7 learnings from this unprecedented year. In this episode you will learn: • Backpain and standing desks [5:41] • The internal conflict model [14:33] • What acceptance really means [38:32] • Intellect and Intelligence [58:10] • Needs vs. wants/desires/wishes [1:08:00] • Intention vs effect [1:25:51] • Do not take things personally [1:46:12] Additional materials: www.superdatascience.com/431

In this episode, I talk about the reasoning behind my decision to step down as the host of the SDS podcast. Additional materials: www.superdatascience.com/430

Jon Krohn joins us for a year-end episode about 2020’s biggest data science breakthroughs and for a big podcast announcement for 2021. In this episode you will learn: • Global warming [4:37] • Our big podcast announcement [6:57] • Who is Jon Krohn? [12:14] • Top 3 technological breakthroughs of the year [21:28] • AlphaFold [23:33] • GPUs [45:51] • GPT-3 [1:00:26] • Wrap up [1:26:40] Additional materials: www.superdatascience.com/429

In this episode, I talk about a very interesting concept around expectations and reality, and how the gap between the two might be affecting us. Additional materials: www.superdatascience.com/428

Syafri Bahar joins us for a great conversation about his work at GOJEK, a decacorn super app bringing services to Indonesia, and his philosophy of empowered data science teams. In this episode you will learn: • Syafri’s day job at GOJEK [11:26] • What is a super app? [14:50] • The data science department at GOJEK [19:47] • High-performance data science team [31:17] • Syafri’s career journey and love of math [39:49] • Apply to work at GOJEK [55:42] • Working for the benefit of others [1:00:21] Additional materials: www.superdatascience.com/427

In this episode, I talk about something profoundly important for me this year in shifting away from ego-driven ambition towards non-materialistic meaning in your life and work. Additional materials: www.superdatascience.com/426

Rama Akkiraju joins us to discuss the past, present, and future of AI services and how companies and data scientists can best prepare themselves to become AI consumers. In this episode you will learn: • 23 years at IBM, before and after data science [6:11] • IBM Watson and AI services [12:25] • Skills to utilize AI services [25:02] • How to achieve significant ROI on AI deployment [41:31] • What does the AI future look like to Rama? [52:41] • Ethics and the benefits of AI [1:04:37] Additional materials: www.superdatascience.com/425

In this episode, we talk about how businesses can maximize their relationship with AI to ensure visible ROI and progress of industries. Additional materials: www.superdatascience.com/424

Amanda Obidike joined us for a great discussion about her work in Nigeria and the African continent in empowering and enabling STEM education and job placement. In this episode you will learn: • Life in Lagos, Nigeria [5:22] • Amanda’s journey to data science [7:28] • Case studies and example projects [13:00] • STEM skills and the start of STEMi [19:41] • What are the issues STEMi is addressing? [24:48] • Get involved in STEMi’s mentoring project [30:12] • STEMi’s results so far [36:02] • Amanda’s best tips for landing jobs [39:04] • Work in promoting education and literacy [45:19] • The progress of STEM in Africa [47:34] Additional materials: www.superdatascience.com/423

In this episode, I talk about the difference between pain and suffering and the importance of becoming aware of it. Additional materials: www.superdatascience.com/422

Theunis Barnard joins us for a great conversation about digital twins and how data scientists can learn about the technology and get involved with its applications. In this episode you will learn: • Data science in South Africa [6:08] • Theunis’s current companies [11:32] • Industry 4.0 [13:59] • Digital twins [22:37] • Theunis’s day-to-day [38:54] • Further examples of digital twins [42:26] • Future of digital twins [48:02] • Theunis’s advice for data science newcomers [57:17] • Process digital twins vs. system digital twins [59:42] Additional materials: www.superdatascience.com/421

In this episode, we do an exercise using the wheel of life to examine your time management and understand how balanced your life currently is. Additional materials: www.superdatascience.com/420

Juval Löwy joins us for an exceptional episode that condenses much of his masterclass teachings into a powerful hour of information about the right approach to designing systems as well as projects. In this episode you will learn: • Career planning [7:24] • Consequences of designing against requirements [8:57] • The framework of a good system design [30:32] • The right approach to project design [44:00] • Juval’s book [1:02:31] • The progress and future [1:03:48] Additional materials: www.superdatascience.com/419

In this episode, I discuss a very interesting quote by Beethoven about the importance of giving space to feelings, even if that means making a mistake. Additional materials: www.superdatascience.com/418

Arthur Shectman joins us to discuss the data engineering and data product development work they do in Elephant Ventures and the importance of capturing value through data. In this episode you will learn: • What is Elephant Ventures? [8:11] • Data quality engineering [21:00] • The importance of focusing on business value [39:58] • Methodology for understanding the company’s business value [46:05] • What is data engineering? [49:28] • What is data product development [51:34] • What are the technical skills needed for these jobs? [56:02] • What is the future bringing for data science? [59:23] Additional materials: www.superdatascience.com/417

In this episode, I talk about the three key ingredients for a successful, happy career in data science. Additional materials: www.superdatascience.com/416

Asieh Ahani joins us to discuss her rapid career progress, the unique work she does at MassMutual, and how she maintains her technical skills while working in a leading position. In this episode you will learn: • Asieh’s background [5:09] • Machine learning techniques for processing biosignals [14:24] • Signal processing [22:22] • Asieh’s career and move from academia to industry [27:19] • Maintaining technical skills as a manager [41:48] • MassMutual is hiring [47:02] • Leading a remote data science team and work/life balance [49:55] • Asieh’s words for other women in data science [55:28] • Future of data science [1:00:30] Additional materials: www.superdatascience.com/415

Today I talked about the importance of understanding the balance between acting selfishly and acting with self-neglect and how the awareness of our needs and wants can help with that. Additional materials: www.superdatascience.com/414

Emmanuel Letouzé discussed in-depth his work in global data science literacy and how he hopes data science will benefit the world in various societal and socio-economic challenges. In this episode you will learn: • Parenting and its effects on Emmanuel’s life and work [3:14] • Why did Data-Pop Alliance come to life? [8:42] • Working with Harvard and MIT [13:04] • Examples of projects and areas of focus [18:16] • Data as lenses and data as lever [29:43] • Sustainable Development Goals indicators [38:21] • How can we use data as a lever? [43:41] • How can data help with disaster resilience? [57:09] • The future of data science [1:04:09] Additional materials: www.superdatascience.com/413

Today I talked with a chiropractor about how to best treat your back while working during the day. Additional materials: www.superdatascience.com/412

Jennifer Cooper talked with us about her role as a strategic analyst and how others can get involved with similar positions around analytics and hybrid roles. In this episode you will learn: • Jennifer’s start in data science [6:04] • What is analytics support function? [16:01] • Keys to success in analytics roles [21:09] • How do you find these roles? [42:42] • DataScienceGO Virtual #2 [50:45] • Common questions Jennifer gets [1:00:52] Additional materials: www.superdatascience.com/411

Today I talk about something important, which I recently had to reteach myself, about personal needs and communication. Additional materials: www.superdatascience.com/410

Steve Nouri talks with us about the importance of managing your personal brand, participating in hackathons, and being active in the conversations around AI as you begin your career. In this episode you will learn: • Steve’s work in the Australian Computer Society [4:32] • River City Labs [12:22] • Hackathons during the pandemic [16:21] • Choosing a path in AI [26:09] • The AI bubble and its implications [31:09] • Strategic data acquisition [38:04] • Explainable AI [43:50] • Creating a personal brand [51:35] Additional materials: www.superdatascience.com/409

Today I talk about an interesting concept that can often be the cause of conflicts in professional and personal relationships. Additional materials: www.superdatascience.com/408

Margot Gerritsen joins us for a great discussion that was both technical and inspiring, on the topics of principal component analysis and linear algebra, as well as the importance of women in data science. In this episode you will learn: • Margot’s travels and background [7:29] • Margot’s position and work at Stanford [13:38] • What is linear algebra? [18:00] • Principle component analysis [23:02] • WIDS, Women in Data Science [32:08] • Margot’s diversity call to action [58:12] • How can men support their female colleagues? [1:05:55] Additional materials: www.superdatascience.com/407

Today we discussed the Buddhist concept “abandon hope” as a way to avoid falling victim to negative emotions and fear. Additional materials: www.superdatascience.com/406

Thomas Obrist joins us to give an advanced talk on the work he does in the financial and energy space as a quant and how it overlaps with data science. In this episode you will learn: • Thomas’s background and studies [5:04] • Long and short in financial markets [8:33] • Thomas’s current role at Axpo [14:55] • Quant vs. data scientist vs. data analyst [18:55] • The Monte Carlo method [26:26] • Thomas’s day-to-day [30:06] • Grid loss use case [35:25] • Thomas’s hackathon success [53:22] • Thomas’s recommendation for those interested in the space [1:01:39] Additional materials: www.superdatascience.com/405

Today we dissect the building blocks of storytelling to help you become a better presenter of your data science insights. Additional materials: www.superdatascience.com/404

Juan Gabriel Gomila Salas joins for an exciting discussion about his work in the game industry and how gamification can boost data science impact across industries. In this episode you will learn: • Juan Gabriel’s work before and during COVID-19 [3:37] • Juan Gabriel’s unique career path [10:36] • Video game monetization case study [25:44] • How can data scientists utilize gamification in their daily jobs? [36:28] • Juan Gabriel’s work as a professor [42:46] • Is online education the future? [47:40] • Data science in the English speaking world vs the Spanish speaking world [52:30] • Where is data science headed? [59:45] Additional materials: www.superdatascience.com/403

In this episode, I discuss an interesting metaphor I’ve recently utilized to help myself face and overcome toxic or negative feelings. Additional materials: www.superdatascience.com/402

Michael Galarnyk joins to tackle your questions on data science job hunting and data science education. In this episode you will learn: • Who is Michael Galarnyk? [3:48] • Tools and skills to know [11:52] • Building and sharing a portfolio [26:21] • Advantages of online and in-person education [37:42] • Teaching data science to younger students [43:55] • Necessary soft skills to be a successful data scientist [51:31] Additional materials: www.superdatascience.com/401

In this anniversary episode, we discuss the importance of knowing why you do data science and how your skills may one day impact the world as challenges arise. Additional materials: www.superdatascience.com/400

Monica Royal joins us to discuss her journey from consumer to contributor in the data science community and how sharing your work and exploring networking can help you on your journey. In this episode you will learn: • Monica’s activity in the data science community [5:17] • The biggest takeaways from Monica’s 100 Days of Learnings [11:00] • Techniques for productivity and continued learning [16:03] • Monica’s interest in the SDS podcast and keeping up to date in data science [33:01] • The DataScienceGO Virtual experience [35:51] • Strategic thinking [38:38] • Monica’s parting inspirational thoughts [41:01] Additional materials: www.superdatascience.com/399

In this episode, I discuss a very important topic on the stages and symptoms of burnout and how to tackle them at each point to avoid irreparable damage. Additional materials: www.superdatascience.com/398

We chatted with data science influencer, educator, and principal data scientist Kirk Borne about his philosophy and work in spreading data science literacy across fields and industries through his frameworks. In this episode you will learn: • Live vs. virtual events [4:20] • Who is Kirk Borne? [7:13] • Big data’s evolution and the emergence of small data [11:17] • The fourth industrial revolution and the future [22:00] • How has the data science education space changed in 14 years? [33:44] • Four types of data discovery [38:00] • The broad categories of AI you should pursue [50:44] • 5 dimensions of analytics implementation [53:50] • LinkedIn Q&A [1:05:00] • Hiring at Booz Allen [1:15:18] Additional materials: www.superdatascience.com/397

In this episode, I share a series of great tips, plus a bonus tip for getting your application further along in the hiring process and getting the job. Additional materials: www.superdatascience.com/396

Cole Nussbaumer Knaflic talks about her influential book Storytelling with Data and shares some best practices for conveying meaning from your visualizations. In this episode you will learn: • Cole’s business Storytelling With Data [4:04] • How did Cole get into this space? [7:24] • When did Cole start writing the book? [15:33] • Top 3 tips from the book [22:44] • How to structure a good story [35:17] • Communicating in-person vs. virtually [41:37] • Cole’s upcoming workshops [43:50] • LinkedIn Q&A [48:57] • Cole’s advice on preparing for the future in the field [1:05:22] Additional materials: www.superdatascience.com/395

In this episode, I discuss the power of teaching what you learn to help you retain the highest amount of the information you are learning. Additional materials: www.superdatascience.com/394

John Peach joins to discuss his passion for bringing more scientific approaches to the data science field, making it smarter and more efficient. In this episode you will learn: • John’s move from Canada to the US [3:37] • John’s new position at Oracle [8:31] • Data Science Workflows [9:34] • John’s solution to data science workflow exploration [12:06] • John’s data science design thinking framework [21:20] • Case study [34:21] • Literate statistical programming [43:12] • R or Python? [51:55] • Data unit testing [53:28] • What drives John? [1:00:56] Additional materials: www.superdatascience.com/393

In this episode, I describe my morning ritual and discuss the importance of setting up a morning ritual for yourself. Additional materials: www.superdatascience.com/392

John Elder joins for an amazing podcast to share his data science "campfire tales" spanning over 20 years of his career in the industry. It will definitely help you in your work to incorporate some of the best principles. In this episode you will learn: • John’s first bungee jump [4:01] • Calculus vs. resampling [14:01] • Elder Research [21:11] • Domain knowledge advice [25:26] • The importance of instincts [41:52] • Ensembles and simplicity [59:33] • John’s opinions on neural nets [1:10:49] • Target shuffling method and the crisis in science [1:17:27] • What does the future of data science hold? [1:39:53] Additional materials: www.superdatascience.com/391

In this episode, I share a tip I came across this week about avoiding conflict in interpersonal relationships. Additional materials: www.superdatascience.com/390

Josh Hortaleza discusses how he’s become a juggernaut of an aspiring data scientist and powered through networking and internships to reach his goals in the field. In this episode you will learn: • How did Kirill and Josh meet [8:26] • Who is Josh? [12:42] • Josh’s first internships [17:07] • Being “good enough” and the luck factor [34:51] • Josh’s goal [40:55] • Genuine networking [43:08] Additional materials: www.superdatascience.com/389

In this episode, I share an awesome tip for anyone at any level around recruitment and headhunters. Additional materials: www.superdatascience.com/388

Lillian Pierson discusses her work on data leadership and how any data scientist can become a data leader in their organization or community. In this episode you will learn: • Who is Lillian Pierson? [3:27] • Winning With Data [6:08] • Four superpowers of great data leaders [11:53] • Benefits of developing these skills [17:27] • Examples of quick win challenges in Winning With Data [19:34] • Impact of COVID-19 [22:23] • Where is the industry going? [28:26] Additional materials: www.superdatascience.com/387

Today, I explain cohort analysis and how this can be used for conversion metrics and tracking the customer journey. Additional materials: www.superdatascience.com/386

T. Scott Clendaniel joins to discuss advanced topics in data science and his forecasts for the future in this field. He also talks about the importance of soft skills for data scientists. In this episode you will learn: • Who is Scott Clendaniel? [6:57] • Scott’s role at Franklin Templeton [10:24] • LinkedIn advanced Q&A [13:29] • Tools that Scott uses the most [26:57] • Target mean encoding technique [30:35] • LinkedIn Q&A on models [33:11] • LinkedIn Q&A on soft skills [54:04] • LinkedIn Q&A on forecasts for the future [01:00:19] • Hub and spoke model in Data Science Management [01:08:32] • Scott’s advice for advanced data scientists [01:10:12] Additional materials: www.superdatascience.com/385

Today, I discuss best practices for data visualization and how to build on what we learned about cognitive load. Additional materials: www.superdatascience.com/384

Sean Casey joins to discuss his data science journey and how he’s used online courses, secondary resources, and the wider network to help his journey to a data visualization professional. In this episode you will learn: • How Sean and Kirill met at DSGO Virtual [4:25] • Sean’s experience at the virtual event [7:32] • Sean’s journey [10:06] • Do you need the credibility of a degree? [22:01] • Sean’s supplemental readings [24:33] • What can others do to replicate Sean’s success? [39:18] • Sean’s advice for others just starting [50:15] Additional materials: www.superdatascience.com/383

Today, I discussed the types of cognitive load and how to best utilize them when imparting information through data. Additional materials: www.superdatascience.com/382

Tony Saldanha joins the podcast to discuss the realities of digital transformation and the steps companies must take to successfully transform in this fourth industrial revolution. In this episode you will learn: • Tony’s book on digital transformation [2:51] • What is digital transformation [8:30] • Five stage framework of going through digital transformation [11:13] • Case studies through the stages [16:43] • Why do digital transformations fail? [27:26] • VC portfolio approach [31:21] • Tony’s consulting work and top tips [40:11] • Change management and COVID-19 [44:44] • Disruption vs. digital transformation [51:14] • What does the future hold? [53:50] Additional materials: www.superdatascience.com/381

Today, I discuss the difference between a data analyst and data scientist and how you can join our team as a potential data analyst. Additional materials: www.superdatascience.com/380

Christopher Bishop speaks on the importance of career tactics in data science and how to prepare and move through the career path you want. In this episode you will learn: • Who is Christopher Bishop? [5:18] • How Christopher developed his advising framework [9:17] • Why data scientists? [12:07] • What is the Future Career Toolkit? [15:54] • How to connect with people as an unknown data scientist [34:09] • What's the intended outcome of the framework? [43:53] Additional materials: www.superdatascience.com/379

In this episode, I talk about the importance of the unconscious mind in decision making and how logic and reasoning may sometimes hinder you. Additional materials: www.superdatascience.com/378

Deborah Berebichez joins us to discuss her experience as a woman in STEM, her work with upcoming generations of women in STEM, and how she helps facilitate data science trainings. In this episode you will learn: • Deborah's origins [4:21] • Pursuing physics as a Jewish-Mexican woman [9:43] • Deborah's work in helping women in STEM [23:10] • How can companies also aid women in STEM? [28:10] • How can individual data scientists work on creative thinking? [44:31] • Deborah's work at Metis [48:26] • Data literacy done the right way [1:00:33] • The future of data science [1:04:55] Additional materials: www.superdatascience.com/377

In this FiveMinuteFriday, I talk about the need to widen your horizons, expose yourself to more varied disciplines and thought processes, and the benefits you can get in your work from doing this. Additional materials: www.superdatascience.com/376

Greg Pavlik joins me for a great talk about the current state of the cloud and how single practitioners and small businesses can take advantage of cloud services. In this episode you will learn: • Will we have cloud-based solutions for VR and working from home? [8:15] • Greg’s career journey [11:50] • From Hadoop to Cloud [23:35] • The cloud element in data science [30:17] • Data science and AI in Oracle [33:00] • Is Oracle more suited for larger companies only? [37:35] • Fundamental differences between Oracle Cloud, Amazon, and Azure [42:12] • Trends in data science and data management [45:14] • Why should someone choose Oracle over any other open source? [52:50] • How does the future of data management look like? [56:00] • 5G and edge computing [1:01:36] • Greg’s recommendation to data scientists [1:04:28] Additional materials: www.superdatascience.com/375

In this episode, I talk about an issue I’ve been having when it comes to phasing my mind out of work and into post-work activities, a concept called “attention residue”. Additional materials: www.superdatascience.com/374

Laurence Moroney sits down to talk about TensorFlow, its community, and his work educating developers in AI and machine learning. We talk about the explosive growth of the community and the great chance for career advancement for all developers, regardless of educational background. In this episode you will learn: • Who is Laurence Moroney? [4:14] • The importance of developers' focus on AI [8:21] • What is TensorFlow and how can it help in AI? [15:53] • Differences in TensorFlow editions [26:26] • Careers and overcoming the fear of AI [31:14] • TensorFlow community [48:46] • What does the future look like? [54:40] Additional materials: www.superdatascience.com/373

Today, I talk about P-value and proper hypothesis testing as well as the importance of statistical significance. Additional materials: www.superdatascience.com/372

Anthony Metivier joins us again for an in-depth discussion about how memory and presence can boost productivity for people in their professional and personal lives. In this episode you will learn: • Anthony’s technique for memorizing names [12:04] • Anthony’s new book and concept of memory [15:45] • Memory and productivity insights [31:44] • Memory palace construction methods [37:30] • How can memory techniques help a data scientist [1:01:30] • Challenge frustration curve [1:07:28] • Further advice and learnings [1:11:59] Additional materials: www.superdatascience.com/371

In today’s FiveMinuteFriday episode, I wanted to experience explaining support vector regression without the use of any visual aids. Additional materials: www.superdatascience.com/370

John Johnson joins me for a thoughtful discussion about the importance of data in the world of economics and business analytics. We discuss his academic and professional history until his work now and how his company is sifting through economic data during the COVID-19 pandemic. In this episode you will learn: • Living and working in Washington D.C. [4:11] • John’s initial jobs before Edgeworth [8:41] • Edgeworth's core values [12:01] • Edgeworth Economics and Edgeworth Analytics case studies [16:57] • Data analytics vs. data science [29:50] • Parachuting into industries [36:06] • Real analytics vs. “lip service” [42:11] • HR business analytics [51:13] • How much, as a business owner, should you rely on a consultant? [56:26] • John’s advice to worried business owners [59:24] Additional materials: www.superdatascience.com/369

Today, I discuss the best ways to ensure you future-proof your career for the great restructuring of the workforce that technological advancements already brought and will bring even more in the future. Additional materials: www.superdatascience.com/368

Samuel Hinton joins us again for an important and timely discussion on data pipelines and the work he’s doing to aid research on COVID-19 with the COVID-19 Critical Care Consortium. We also talk about his new online courses and his continued research into dark matter. In this episode you will learn: • Sam’s current work and COVID-19 Critical Care Consortium [4:22] • The COVID data science pipeline and workflow [12:50] • Sam’s second online course [36:22] • Bayesian inference [43:06] • Sam at DSGO Virtual [53:30] • Sam’s work on dark matter [1:01:25] • What is Sam reading right now? [1:09:14] Additional materials: www.superdatascience.com/367

Today, I discuss a profound conversation we had with our team this month on success and how you can define your own success. Additional materials: www.superdatascience.com/366

Jon Krohn joins me to discuss his work at untapt in designing models for HR purposes. We also discuss the power of data science across fields of medicine and epidemiology, as well as the future of deep learning. In this episode you will learn: • Coronavirus update in New York City [2:36] • What brought Jon to New York? [5:38] • Data science and coronavirus [12:50] • Jon’s work at untapt [18:09] • Techniques used to design models in untapt [22:02] • untapt’s approach to explainability and bias [30:19] • Jon’s other contributions to data science [38:10] • Jon’s book and visual teaching styles [44:32] • LinkedIn Q&A [52:05] • Jon’s recommendation for becoming best at deep learning [1:13:09] Additional materials: www.superdatascience.com/365

Today, I’m talking with Anthony Metivier about practices to help your brain and body, work through the stress of the pandemic. Additional materials: www.superdatascience.com/364

Piyanka Jain goes in-depth about the true power of data that can be unlocked when you combine intuition with data science practices and follow a hypothesis-driven framework to reach your project goals. Items mentioned in this podcast: • The power of data plus intuition [5:29] • BADIR framework for data science [12:36] • What can students pick up from Aryng’s courses? [24:58] • SWAT data science teams [34:16] • The rate of successful projects [39:38] • Four D’s of Data Culture [45:27] • Decision science vs data science [49:17] • Piyanka’s inspiration for her book [51:23] Additional materials: www.superdatascience.com/363

Today, I’m talking about an interesting topic I found in our own Data Science newsletter about the need for hybrid AI models in the future. Additional materials: www.superdatascience.com/362

John David Ariansen joins me for an episode on the best practices for getting into data science consulting, the importance of understanding data science and analytics, and how you can network, even during a pandemic. In this episode you will learn: • Coronavirus and how it will affect the way we work [3:06] • John David’s consulting work [8:19] • Why did John get into consulting? [13:17] • Does John David’s age affect his clients? [25:03] • John David’s podcast [34:59] • The difference between data science and analytics [40:26] • Creating space for opportunities [49:54] • 3 top tips for getting a job in data science [54:28] Additional materials: www.superdatascience.com/361

In this episode, I’m exploring some topics in proper sleep habits to help you keep good sleep schedules. Additional materials: www.superdatascience.com/360

Emily Robinson breaks down her new book “Build a Career in Data Science” by sharing what skills she focuses on exploring, who the data science field is for, and how to tackle interviews and negotiations. In this episode you will learn: • Long-distance networking [5:58] • Emily’s book [9:38] • Who is the field of data science for? [14:02] • Should newcomers use Python or R? [23:34] • Five company archetypes [28:36] • Approaching data science interviews and negotiating [31:25] • How do you actually get an interview? [48:08] • Emily at DSGO 2020 [57:07] • Emily’s final take-home message [58:52] • Where to buy Emily’s book and SDS discount code [1:04:26] Additional materials: www.superdatascience.com/359

In this episode, I’m discussing my personal experience with discrimination during a trip at the start of the pandemic and how it elevated my understanding of racism and discrimination beyond just a cognitive level. Additional materials: www.superdatascience.com/358

Tracy Crossley, a Behavioral Relationship Expert, talks about how you can explore yourself during this difficult time. We also explored how different relationship dynamics can be tested during a forced lockdown and how to avoid dangerous emotional pitfalls. In this episode you will learn: • What work does Tracy do? [5:50] • Tracy’s training [8:20] • Tracy’s view on the consequences of the pandemic [12:55] • Ways to tackle emotions during lockdown [17:14] • Final advice to those struggling during lockdown [1:00:11] Additional materials: www.superdatascience.com/357

Today, I’m helping you explore working remotely. Whether you’ve started doing this during the pandemic or you've been interested in and exploring remote-based jobs recently. I outline three advantages and three disadvantages to consider. Additional materials: www.superdatascience.com/356

DJ Patil talks about ethics in data science and the importance of data science communities working together to make sure data science is an accelerant of solutions for our children and our children’s children. In this episode you will learn: • How does it feel to be the person who created data science as we know it now? [3:17] • What data science is not [6:01] • Ethics and data science development in different countries [10:00] • What is the “biorevolution”? [16:02] • The importance of data sharing [20:10] • The current state of Chief Data Scientist of USA [24:07] • LinkedIn Q&A [26:03] • What to think about when you think about data science [44:08] Additional materials: www.superdatascience.com/355

Today I discuss a negative coefficient as a philosophical concept in problem-solving in your life. Do you make things worse by ignoring a problem or doing the wrong things to fix it? Additional materials: www.superdatascience.com/354

Brian T. O’Neill joins me for an insightful dive into how you can implement human-centric practices into your data work, whether you’re a consultant or individual contributor. There are ways and steps to workshop best practices in conversations with stakeholders. In this episode you will learn: • Brian’s two lives [7:28] • Brian’s human-first focal point [10:05] • The process of Brian’s consulting work [17:07] • How can an individual contributor be better at design thinking? [40:43] • Walkthrough Brian’s course and seminar [54:37] Additional materials: www.superdatascience.com/353

Today, we’re diving into our fifth and final part of our history of data science series by looking into data science’s future through the eyes of five of the most influential people in our space and how they see the next few decades. Additional materials: www.superdatascience.com/352

Stratos Hadjioannou is a freshly hired data scientist who is self-taught and made the jump to visit DSGO. He talks about his learnings, putting himself in a data science ecosystem, and how to tackle interviews with little experience. In this episode you will learn: • Where did Stratos start? [6:16] • How to keep the momentum for learning [12:20] • Stratos’s goals [19:35] • Planning the steps to getting a data science job [23:01] • Triad for successful interviews [32:47] • Application process [34:53] • Experiences from the first data science job [45:51] Additional materials: www.superdatascience.com/351

Today, we take some time to discuss the real mental and emotional toll social distancing can take during the coronavirus. How can we effectively tackle each other's needs during this period? Additional materials: www.superdatascience.com/350

Brad Klingenberg talks about the unique way Stitch Fix uses algorithms and human-in-the-loop AI to generate excellent customer experiences and pull ahead of other retailers in the space. In this episode you will learn: • Working in Stitch Fix [5:18] • How does Stitch Fix work? [11:29] • Stitch Fix algorithms tour [20:14] • Open positions in Stitch Fix [36:25] • Stitch Fix takeaways for other companies [39:07] • Humans + machines [44:19] • Stitch Fix global expansion [47:34] • Future of personalization [50:16] • Brad’s advice to data scientists [55:33] Additional materials: www.superdatascience.com/349

In the penultimate episode of our history of data science series, we look at 2015 on and watch as data science goes from being about hard skills and coding to being about ethics and progress. Additional materials: www.superdatascience.com/348

Kerri Twigg talks with me about her work in helping professionals talk about themselves and tell stories about their passions and professional work to land ideal jobs and propel their career trajectory. In this episode you will learn: • Kerri at DSGO 2019 [6:09] • Who is Kerri Twigg? [8:00] • A case study from DSGO 2019 [9:51] • How do you build a career story? [18:30] • Kerri’s book and practices [32:35] • How to prepare for interviews [43:22] • 3-Parts of a career story [56:53] Additional materials: www.superdatascience.com/347

In this FiveMinuteFriday we take a break from our series on the history of data science to discuss productivity and my top 5 hacks for getting more hours out of your day and week. Additional materials: www.superdatascience.com/346

I speak with Dan Shiebler who works as a machine learning engineer at Twitter Cortex and at the same time, is doing a Ph.D. on applying category theory in machine learning. We discuss his work at Twitter, the importance of academics, and the future of machine learning. In this episode you will learn: • What is great about Twitter [5:31] • Dan’s Ph.D. program [9:25] • Dan’s work at Twitter [18:07] • Dan at DSGO 2020 [35:16] • LinkedIn Q&A [40:25] • Dan’s advice [1:03:58] Additional materials: www.superdatascience.com/345

In the third of five episodes in this series, I journey through 2010 into 2015 to look at the boom of self-driving cars, the growth of data science as a profession, and the beginning of educational paths for future data scientists. Additional materials: www.superdatascience.com/344

I speak with Jose Quesada, founder and CEO of Data Science Retreat about the purpose of his program to help data scientists learn and find jobs through a three-month retreat and portfolio project. In this episode you will learn: • Overview of Jose’s current projects [5:55] • "What if I don’t have a tech background?" [09:58] • How does it work? [11:51] • Program structure [21:24] • Tips for picking a portfolio project [26:45] • The program’s next intake [1:03:06] Additional materials: www.superdatascience.com/343

In the second of five episodes in this series, I take a step into the early 2000s and the true boom of data science as a profession and philosophy of study, as well as look at some of science fiction’s failed hopes for data science by this time. Additional materials: www.superdatascience.com/342

Brandon Rohrer joins me in this special episode about robotics, machine learning, and the merge of software and hardware to create innovative technology for homes around the world. In this episode you will learn: • Brandon at MIT [7:41] • iRobot [15:14] • Moving from Facebook to iRobot [17:14] • Brandon’s work in iRobot [20:18] • Brandon as a data science influencer [30:08] • Q&A [40:40] Additional materials: www.superdatascience.com/341

In this five-episode series, I dive into the history of data science from the beginning of mathematics to today. In this first episode, we start by looking in the 1950s and go up to the dawn of the 2000s. Additional materials: www.superdatascience.com/340

I sat down with my coach Ivor Lok to discuss the power and importance of coaching and how everyone can use it in their personal and professional lives to become happier. In this episode you will learn: • Managing expectations [9:21] • Personal beliefs & parenting [17:42] • Value of having a coach [25:33] • Mindset over skillset [37:24] • Dream lists [51:06] • Ivor’s new projects [1:03:20] Additional materials: www.superdatascience.com/339

I discuss an observation I had recently about how many photos we take, and how much we miss out on by focusing on capturing a moment rather than living it. Additional materials: www.superdatascience.com/338

Hadley Wickham, a huge presence in data science, sits down to talk about R, Python, and the future of potential integrations, as well as some Q&A with our listeners through LinkedIn about programming languages and how to make data science accessible for all. In this episode you will learn: • Hadley’s R packages [8:26] • Better integrations between R and Python [20:11] • LinkedIn Q&A [33:34] • useR Conference vs. RStudio Conference [50:46] • LinkedIn Q&A: Career-related questions [1:01:06] • LinkedIn Q&A: Future-related questions [1:08:01] Additional materials: www.superdatascience.com/337

I discuss something that popped up for me recently: is it better to have something finished or to have something be perfect? I explore the answer and what it can mean for you in your life. Additional materials: www.superdatascience.com/336

Rico Meinl failed when he tried to make a successful startup. He learned a lot from it and shared his story and learnings for nearly 2 hours in one of our longest and most insightful podcasts to date. In this episode you will learn: • Rico at DSGO [8:50] • Dresswell [17:10] • B2B vs B2C in startups [34:03] • Rico's 5 learnings [53:25] • Learning no. 1 [53:54] • Learning no. 2 [56:33] • Learning no. 3 [1:10:43] • Learning no. 4 [1:24:08] • Learning no. 5 [1:34:02] • Rico’s next steps [1:45:35] Additional materials: www.superdatascience.com/335

I return to the concept of no coaching in more detail and discuss how I recently had a good conversation with a friend without giving advice but offering empathy. Additional materials: www.superdatascience.com/334

Sinan Ozdemir is back again, this time talking about his work since his company Kylie.ai was acquired by Directly. We discuss his work, the way he is creating human and AI synergy and the future of NLP as it continues to progress. In this episode you will learn: • Sinan’s company acquired [7:29] • Explainable deep learning models [16:13] • Airbnb case study [19:42] • Microsoft case study [22:25] • Sinan’s role at Directly [25:57] • Work with Sinan [32:57] • Preview of Sinan at DSGO [38:38] • BERT [43:18] • Sinan’s prediction for NLP in 2020 [53:17] Additional materials: www.superdatascience.com/333

I discuss the concept of putting yourself on autopilot and powering through getting work done when you feel like giving up. Additional materials: www.superdatascience.com/332

Harshal Sanap talks about how he took himself from a data science student and graduate to a full time professional in data science and shares mistakes to avoid to get started in your career. In this episode you will learn: • Harshal at DSGO [8:12] • Harshal’s first data science job [16:01] • The process of getting your first job [21:25] • 3 steps to data science job search [23:37] • 4 tips on how to apply for jobs [36:59] • 5 tips on how to prepare for an interview [53:21] • 5 mistakes to avoid [1:10:31] Additional materials: www.superdatascience.com/331

I discuss finding the good in something that is objectively not so good and how you can take setbacks as a learning experience and challenge. Additional materials: www.superdatascience.com/330

Isaac Reyes talks about his approach to data visualization. We dive into the science behind it, the psychology, and the needs in businesses for proper and informed data storytelling. • Catching up with Isaac [6:37] • StoryIQ's office in Manila [10:04] • What is data storytelling? [12:29] • The keys to data storytelling [15:47] • Second key to data storytelling [18:36] • Third key to data storytelling [21:35] • Elementary Perceptual Tasks Scale [24:10] • Gestalt principles [38:56] • How does StoryIQ teach this? [48:35] • Fourth key to data storytelling [49:20] Additional materials: www.superdatascience.com/329

In this week’s FiveMinuteFriday, I wish you all a happy New Year with an interesting story about having the choice to see the best in situations or see the worst in them. Additional materials: www.superdatascience.com/328

Hadelin and I outlined our top 5 trends in Data Science for 2020. We discussed why they’re hot topics and how companies can utilize them to drive profit and efficiency in the coming year. In this episode you will learn: • The decade in review [1:45] • A decade preview [5:20] • 2020 trends webinar [7:30] • Robotic process automation [9:00] • Natural language processing [18:28] • Reinforcement learning [26:35] • Edge computing [37:25] • Open source AI frameworks [52:02] Additional materials: www.superdatascience.com/327

This week’s FiveMinuteFriday and final episode of 2019 is about who inspires you and how it may be those closest to you without you even realizing it. Additional materials: www.superdatascience.com/326

I went over the 7 top learnings I took from this exciting year of ups, downs, and incredible adventures and explorations. In this episode you will learn: • Dichotomies [6:18] • F*ck FOMO [19:00] • Full circle stress [27:23] • Letting doors close [38:57] • Managing my energy as an introvert [45:00] • No coaching [56:15] • Feelings [1:03:38] Additional materials: www.superdatascience.com/325

In this week’s FiveMinuteFriday, Vitaly and I talked more about a familiar topic: proximity is power. We discussed the importance of connection, how to not saturate, and how to decide with whom you spend your time. Additional materials: www.superdatascience.com/324

I chatted with top Upwork freelancer Wesley Engers who has worked over 150 jobs in data science. He’s worked in a variety of industries and shared a few of his most interesting jobs and offered advice for those considering diving into freelance data science work. In this episode you will learn: • Wesley on Upwork [9:11] • Wesley’s background [16:20] • How Wesley onboards a client [26:32] • Good clients vs. bad clients [31:12] • Tools [37:23] • Wesley’s best projects [45:09] • Freelance vs. full-time work [59:26] • Tips about getting into Upwork [1:06:48] Additional materials: www.superdatascience.com/323

In this week’s FiveMinuteFriday we are with Vitaly and Hadelin again and we are discussing our diets and how we maintain feeling healthy and good through food intake. Additional materials: www.superdatascience.com/322

I sat down with Morgan Mendis whom I met at DSGO this year. He is one of the most advanced data scientists I’ve met and he’s been using his skills and experience to give back to his community. We discuss his career, his dreams, his ideology, and his hunt for a VP of Data Science at his former company. In this episode you will hear: • Catch up since DSGO 2019 [8:04] • VP of Data Science at Inspire [12:00] • Morgan’s career dreams [22:04] • Morgan’s experience [30:50] • Tools & solutions [1:01:33] • How you can get involved [1:12:45] Additional materials: www.superdatascience.com/321

In this week’s FiveMinuteFriday I sat down with Vitaly and Hadelin to discuss the concept of mentorship and how we work through our professional and personal hurdles with mentors. Additional materials: www.superdatascience.com/320

I sat down with Jonathan and Ogo, two DataScienceGO attendees, who are experts in the field of data visualization. Their methods and backgrounds differ but ultimately they believe in the same goal: telling a meaningful story. Additional materials: www.superdatascience.com/319

In this week’s FiveMinuteFriday I discuss the concept of “fake it until you become it” and use of the word “amazing” when thinking about your current state and when people ask how you are. Additional materials: www.superdatascience.com/318

An incredible young guest is in this episode after he attended DSGO. Edis is a 15-year-old, building his own neural networks. We discussed his background, his process of building neural networks from scratch, Kaggle competitions, and the benefit of online data science education. Additional materials: www.superdatascience.com/317

In this week’s FiveMinuteFriday I discuss how best to handle disagreements by keeping your focus on yourself and your own actions. Additional materials: www.superdatascience.com/316

Back by popular demand is Gabriela de Queiroz to discuss various data accessibility issues and how her work, talks, and organizations are working to make data science and AI more available across the board. Additional materials: www.superdatascience.com/315

I asked the team what was one wish they had for our students on their data science journey. The answers are inspirational and encouraging for students at all levels. Additional materials: www.superdatascience.com/314

Marco Caviezel’s journey from research-based psychology into a career as a data analyst is really fascinating. He did his entire data education online and managed to not only teach himself in topics of machine learning and data visualization but got a job as a data analyst through his own work. Additional materials: www.superdatascience.com/313

Kirill and Mitja share some thoughts about one of the workshops at the SuperDataScience offsite retreat. They explore the practice of contemplation as a way to get a deeper understanding and insights. Additional materials: www.superdatascience.com/312

This episode with Daniel Obodovski explores smart cities and the importance of problem-solving from city to city by using data correctly. But solutions aren’t always obvious, privacy continues to be a huge issue for citizens, and not every city prioritizes problems the same way. It’s a fascinating topic. Additional materials: www.superdatascience.com/311

Kirill and Mitja share thoughts on purposeful “trials by fire” in your life and how you can force yourself to grow through intended adversity. Additional materials: www.superdatascience.com/310

A conversation between rival online educators in the data science community about the challenges of creating a worldwide community with millions of students, the trends in data science, and how education can keep up to date. Additional materials: www.superdatascience.com/309

A FiveMinuteFriday about the importance of belonging and how a connection to the larger community in the work that you do can be incredibly beneficial and meaningful for both your career and personal happiness. Additional materials: www.superdatascience.com/308

Kirill and Marc have a conversation that started as a quick FiveMinuteFriday discussion on thoughtfulness that turned into a full podcast worth of content on the power of thought, mindfulness, practice, and how even data scientists need to look past facts and information and follow their intuition. Additional materials: www.superdatascience.com/307

The Costa Rican phrase "Pura Vida" is something very important to think about because it is incredibly beautiful, filled with emotion and it is so powerful. What meaning would this phrase have for you, in your life? Additional materials: www.superdatascience.com/306

Jean-Pierre Labuschagne's career journey started in South Africa and moved to Europe, where he is bringing massive value with the power of data visualization. He is also teaching successful courses online after spending 2 years as a student of online courses himself. Additional materials: www.superdatascience.com/305

Can you think of examples when the law of attraction worked in your life? If you enjoyed this episode, check out show notes, resources, and more at www.superdatascience.com/304

In this episode of the SuperDataScience Podcast, I chat with Astrophysicist and Online Data Science Instructor, Sam Hinton. You will hear about the Lindau Nobel Laureates meeting, where he met Nobel Prize winners and you will also hear about his appearance on the Survivor TV show. You will learn about quantum mechanics. You will also learn about the course he launched in Python for Statistical Analysis, as well as going in-depth on hypothesis testing. You will hear about Python versus R, statistical significance, why p-value of 0.5 is bad, Bayesian statistics, and what is the difference between frequentist and Bayesian approaches. If you enjoyed this episode, check out show notes, resources, and more at www.superdatascience.com/303

What is Data Science to you? If you enjoyed this episode, check out show notes, resources, and more at www.superdatascience.com/302

In this episode of the SuperDataScience Podcast, I chat with Data Scientist at TD Bank, Ayobami Ayodeji. You will hear Ayobami's valuable insights about the takeaways from DataScienceGO 2019, including productization of data science products, the 3 types of data science teams, and building character and resilience. You will also learn about Ayobami's career journey from project manager to data scientist and the sacrifices he made on that journey. If you enjoyed this episode, check out show notes, resources, and more at www.superdatascience.com/301

What are you leaving for the next generation on this planet? If you enjoyed this episode, check out show notes, resources, and more at www.superdatascience.com/300

In this episode of the SuperDataScience Podcast, I chat with Head of Data Science and Machine Learning, Michelle Keim. You will hear what working remotely is all about in data science. You will learn about the importance of failure, and why everyone should lose their job at least once. You will hear about churn and segmentation, what they meant 10 years ago and what they mean now. You will also learn about the imposter syndrome and what to do when you feel like an imposter while applying for a role. You will hear about moving from centralized data science teams to integrated experts within the business and leading people on the three key learnings that Michelle has taken away from her experience as a leader. If you enjoyed this episode, check out show notes, resources, and more at www.superdatascience.com/299

What would you change about the things you do in your life if you thought you only had 6 months to live? If you enjoyed this episode, check out show notes, resources, and more at www.superdatascience.com/298

In this episode of the SuperDataScience Podcast, I chat with data scientist Ayodele Odubela. You will hear how and why she chose to do a Masters in Data Science and supplemented that with online education. You will also hear about self-discovery, fortitude and passion, and how she got one of her data science jobs through Twitter. You will learn about some of Ayodele's projects like using SVM for detecting poisonous vs. edible mushrooms, using random forests and decision trees for ranking wines based on the chemical contents, using the Naive Bayes to detect spam. You will learn about the real-world project that she's worked on, bullet stopping flying drones. You will find out what role machine learning played in that project and how they're going to be applied in society once they get rolled out. If you enjoyed this episode, check out show notes, resources, and more at www.superdatascience.com/297

Do you take time to reflect on who you became or actions you took while on a path to achieving a goal? If you enjoyed this episode, check out show notes, resources, and more at www.superdatascience.com/296

In this episode of the SuperDataScience Podcast, I chat with my friend and business partner, Hadelin de Ponteves. You will hear what new exciting things are happening in Hadelin's life now. You will hear some preview of his upcoming presentation at DataScienceGO 2019, which will cover NLP, especially the BERT model, which raised a whole new level in NLP. You will also learn about reinforcement learning and Hadelin's new course on Twin-Delayed DDPG. If you enjoyed this episode, check out show notes, resources, and more at www.superdatascience.com/295

What about AI worries you in the professional world? If you enjoyed this episode, check out show notes, resources, and more at www.superdatascience.com/294

In this episode of the SuperDataScience Podcast, I chat with Data Scientist, Peyman Hesami. You will find out what reinforcement learning is and how it works on an intuitive level. You will hear about the differences between reinforcement learning versus classification, or other supervised learning methods, and how it's used for personalization specifically. You will learn about six distinct advantages of reinforcement learning, what role reinforcement learning is going to play in the future of machine learning and why. Also, you will find out how and why Peyman made a career transition to work for a startup, how he's using reinforcement learning, and what is the biggest mistake he has made with reinforcement learning. If you enjoyed this episode, check out show notes, resources, and more at www.superdatascience.com/293

How can you find a way to balance your energy through recharging in the way that works best for you? If you enjoyed this episode, check out show notes, resources, and more at www.superdatascience.com/292

In this episode of the SuperDataScience Podcast, I chat with founder and CEO at Daisy Intelligence, Gary Saarenvirta. You'll learn about dangerous implicit assumptions, the power of theory and theory versus data. You'll also learn about two types of decisions, the spacial interaction model, traffic flow model, the concept of dividing the world in two and what humans should be doing, and what artificial intelligence should be doing. You will hear about the difference between artificial intelligence that leverages just data versus artificial intelligence that leverages theory and data, and what advantages that creates. If you enjoyed this episode, check out show notes, resources, and more at www.superdatascience.com/291

How does your inner voice compare to your passions? If you enjoyed this episode, check out show notes, resources, and more at www.superdatascience.com/290

In this episode of the SuperDataScience Podcast, I chat with top AI influencer, Ben Taylor. You will learn some very cool concepts about artificial intelligence such as active adverse impact mitigation, what that means and how that can help train on your dataset without bias. You will hear about AI ethics, deepfakes and Ben's current passion project, building an artificial intelligence that plays Call of Duty, which he will actually demonstrate at DataScienceGO this year at the end of September. If you enjoyed this episode, check out the video, show notes, resources, and more at www.superdatascience.com/289