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Sep 11, 2019
Jordan
Feb 18, 2019
Dec 25, 2018
Episode | Date |
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So long, and thanks for all the fish
|
Jul 26, 2020 |
A Reality Check on AI-Driven Medical Assistants
|
Jul 19, 2020 |
A Data Science Take on Open Policing Data
|
Jul 13, 2020 |
Procella: YouTube's super-system for analytics data storage
|
Jul 06, 2020 |
The Data Science Open Source Ecosystem
|
Jun 29, 2020 |
Rock the ROC Curve
|
Jun 21, 2020 |
Criminology and Data Science
|
Jun 15, 2020 |
Racism, the criminal justice system, and data science
|
Jun 07, 2020 |
An interstitial word from Ben
|
Jun 05, 2020 |
Convolutional Neural Networks
|
May 31, 2020 |
Stein's Paradox
|
May 24, 2020 |
Protecting Individual-Level Census Data with Differential Privacy
|
May 18, 2020 |
Causal Trees
|
May 11, 2020 |
The Grammar Of Graphics
|
May 04, 2020 |
Gaussian Processes
|
Apr 27, 2020 |
Keeping ourselves honest when we work with observational healthcare data
|
Apr 20, 2020 |
Changing our formulation of AI to avoid runaway risks: Interview with Prof. Stuart Russell
|
Apr 13, 2020 |
Putting machine learning into a database
|
Apr 06, 2020 |
The work-from-home episode
|
Mar 29, 2020 |
Understanding Covid-19 transmission: what the data suggests about how the disease spreads
|
Mar 23, 2020 |
Network effects re-release: when the power of a public health measure lies in widespread adoption
|
Mar 15, 2020 |
Causal inference when you can't experiment: difference-in-differences and synthetic controls
|
Mar 09, 2020 |
Better know a distribution: the Poisson distribution
|
Mar 02, 2020 |
The Lottery Ticket Hypothesis
|
Feb 23, 2020 |
Interesting technical issues prompted by GDPR and data privacy concerns
|
Feb 17, 2020 |
Thinking of data science initiatives as innovation initiatives
|
Feb 10, 2020 |
Building a curriculum for educating data scientists: Interview with Prof. Xiao-Li Meng
|
Feb 02, 2020 |
Running experiments when there are network effects
|
Jan 27, 2020 |
Zeroing in on what makes adversarial examples possible
|
Jan 20, 2020 |
Unsupervised Dimensionality Reduction: UMAP vs t-SNE
|
Jan 13, 2020 |
Data scientists: beware of simple metrics
|
Jan 05, 2020 |
Communicating data science, from academia to industry
|
Dec 30, 2019 |
Optimizing for the short-term vs. the long-term
|
Dec 23, 2019 |
Interview with Prof. Andrew Lo, on using data science to inform complex business decisions
|
Dec 16, 2019 |
Using machine learning to predict drug approvals
|
Dec 08, 2019 |
Facial recognition, society, and the law
|
Dec 02, 2019 |
Lessons learned from doing data science, at scale, in industry
|
Nov 25, 2019 |
Varsity A/B Testing
|
Nov 18, 2019 |
The Care and Feeding of Data Scientists: Growing Careers
|
Nov 11, 2019 |
The Care and Feeding of Data Scientists: Recruiting and Hiring Data Scientists
|
Nov 04, 2019 |
The Care and Feeding of Data Scientists: Becoming a Data Science Manager
|
Oct 28, 2019 |
Procella: YouTube's super-system for analytics data storage
|
Oct 21, 2019 |
Kalman Runners
|
Oct 13, 2019 |
What's *really* so hard about feature engineering?
|
Oct 06, 2019 |
Data storage for analytics: stars and snowflakes
|
Sep 30, 2019 |
Data storage: transactions vs. analytics
|
Sep 23, 2019 |
GROVER: an algorithm for making, and detecting, fake news
|
Sep 16, 2019 |
Data science teams as innovation initiatives
|
Sep 09, 2019 |
Can Fancy Running Shoes Cause You To Run Faster?
|
Sep 01, 2019 |
Organizational Models for Data Scientists
|
Aug 25, 2019 |
Data Shapley
|
Aug 19, 2019 |
A Technical Deep Dive on Stanley, the First Self-Driving Car
|
Aug 12, 2019 |
An Introduction to Stanley, the First Self-Driving Car
|
Aug 05, 2019 |
Putting the "science" in data science: the scientific method, the null hypothesis, and p-hacking
|
Jul 29, 2019 |
Interleaving
|
Jul 22, 2019 |
Federated Learning
|
Jul 14, 2019 |
Endogenous Variables and Measuring Protest Effectiveness
|
Jul 07, 2019 |
Deepfakes
|
Jul 01, 2019 |
Revisiting Biased Word Embeddings
|
Jun 24, 2019 |
Attention in Neural Nets
|
Jun 17, 2019 |
Interview with Joel Grus
|
Jun 10, 2019 |
Re - Release: Factorization Machines
|
Jun 03, 2019 |
Re-release: Auto-generating websites with deep learning
|
May 27, 2019 |
Advice to those trying to get a first job in data science
|
May 19, 2019 |
Re - Release: Machine Learning Technical Debt
|
May 12, 2019 |
Estimating Software Projects, and Why It's Hard
|
May 05, 2019 |
The Black Hole Algorithm
|
Apr 29, 2019 |
Structure in AI
|
Apr 21, 2019 |
The Great Data Science Specialist vs. Generalist Debate
|
Apr 15, 2019 |
Google X, and Taking Risks the Smart Way
|
Apr 08, 2019 |
Statistical Significance in Hypothesis Testing
|
Apr 01, 2019 |
The Language Model Too Dangerous to Release
|
Mar 25, 2019 |
The cathedral and the bazaar
|
Mar 17, 2019 |
AlphaStar
|
Mar 11, 2019 |
Are machine learning engineers the new data scientists?
|
Mar 04, 2019 |
Interview with Alex Radovic, particle physicist turned machine learning researcher
|
Feb 25, 2019 |
K Nearest Neighbors
|
Feb 17, 2019 |
Not every deep learning paper is great. Is that a problem?
|
Feb 11, 2019 |
The Assumptions of Ordinary Least Squares
|
Feb 03, 2019 |
Quantile Regression
|
Jan 28, 2019 |
Heterogeneous Treatment Effects
|
Jan 20, 2019 |
Pre-training language models for natural language processing problems
|
Jan 14, 2019 |
Facial Recognition, Society, and the Law
|
Jan 07, 2019 |
Re-release: Word2Vec
|
Dec 31, 2018 |
Re - Release: The Cold Start Problem
|
Dec 23, 2018 |
Convex (and non-convex) Optimization
|
Dec 17, 2018 |
The Normal Distribution and the Central Limit Theorem
|
Dec 09, 2018 |
Software 2.0
|
Dec 02, 2018 |
Limitations of Deep Nets for Computer Vision
|
Nov 18, 2018 |
Building Data Science Teams
|
Nov 12, 2018 |
Optimized Optimized Web Crawling
|
Nov 04, 2018 |
Optimized Web Crawling
|
Oct 28, 2018 |
Better Know a Distribution: The Poisson Distribution
|
Oct 22, 2018 |
Searching for Datasets with Google
|
Oct 15, 2018 |
It's our fourth birthday
|
Oct 08, 2018 |
Gigantic Searches in Particle Physics
|
Sep 30, 2018 |
Data Engineering
|
Sep 24, 2018 |
Text Analysis for Guessing the NYTimes Op-Ed Author
|
Sep 16, 2018 |
The Three Types of Data Scientists, and What They Actually Do
|
Sep 09, 2018 |
Agile Development for Data Scientists, Part 2: Where Modifications Help
|
Aug 26, 2018 |
Agile Development for Data Scientists, Part 1: The Good
|
Aug 19, 2018 |
Re - Release: How To Lose At Kaggle
|
Aug 13, 2018 |
Troubling Trends In Machine Learning Scholarship
|
Aug 06, 2018 |
Can Fancy Running Shoes Cause You To Run Faster?
|
Jul 29, 2018 |
Compliance Bias
|
Jul 22, 2018 |
AI Winter
|
Jul 15, 2018 |
Rerelease: How to Find New Things to Learn
|
Jul 08, 2018 |
Rerelease: Space Codes
|
Jul 02, 2018 |
Rerelease: Anscombe's Quartet
|
Jun 25, 2018 |
Rerelease: Hurricanes Produced
|
Jun 18, 2018 |
GDPR
|
Jun 11, 2018 |
Git for Data Scientists
|
Jun 03, 2018 |
Analytics Maturity
|
May 20, 2018 |
SHAP: Shapley Values in Machine Learning
|
May 13, 2018 |
Game Theory for Model Interpretability: Shapley Values
|
May 07, 2018 |
AutoML
|
Apr 30, 2018 |
CPUs, GPUs, TPUs: Hardware for Deep Learning
|
Apr 23, 2018 |
A Technical Introduction to Capsule Networks
|
Apr 16, 2018 |
A Conceptual Introduction to Capsule Networks
|
Apr 09, 2018 |
Convolutional Neural Nets
|
Apr 02, 2018 |
Google Flu Trends
|
Mar 26, 2018 |
How to pick projects for a professional data science team
|
Mar 19, 2018 |
Autoencoders
|
Mar 12, 2018 |
When Private Data Isn't Private Anymore
|
Mar 05, 2018 |
What makes a machine learning algorithm "superhuman"?
|
Feb 26, 2018 |
Open Data and Open Science
|
Feb 19, 2018 |
Defining the quality of a machine learning production system
|
Feb 12, 2018 |
Auto-generating websites with deep learning
|
Feb 04, 2018 |
The Case for Learned Index Structures, Part 2: Hash Maps and Bloom Filters
|
Jan 29, 2018 |
The Case for Learned Index Structures, Part 1: B-Trees
|
Jan 22, 2018 |
Challenges with Using Machine Learning to Classify Chest X-Rays
|
Jan 15, 2018 |
The Fourier Transform
|
Jan 08, 2018 |
Statistics of Beer
|
Jan 02, 2018 |
Re - Release: Random Kanye
|
Dec 24, 2017 |
Debiasing Word Embeddings
|
Dec 18, 2017 |
The Kernel Trick and Support Vector Machines
|
Dec 11, 2017 |
Maximal Margin Classifiers
|
Dec 04, 2017 |
Re - Release: The Cocktail Party Problem
|
Nov 27, 2017 |
Clustering with DBSCAN
|
Nov 20, 2017 |
The Kaggle Survey on Data Science
|
Nov 13, 2017 |
Machine Learning: The High Interest Credit Card of Technical Debt
|
Nov 06, 2017 |
Improving Upon a First-Draft Data Science Analysis
|
Oct 30, 2017 |
Survey Raking
|
Oct 23, 2017 |
Happy Hacktoberfest
|
Oct 16, 2017 |
Re - Release: Kalman Runners
|
Oct 09, 2017 |
Neural Net Dropout
|
Oct 02, 2017 |
Disciplined Data Science
|
Sep 25, 2017 |
Hurricane Forecasting
|
Sep 18, 2017 |
Finding Spy Planes with Machine Learning
|
Sep 11, 2017 |
Data Provenance
|
Sep 04, 2017 |
Adversarial Examples
|
Aug 28, 2017 |
Jupyter Notebooks
|
Aug 21, 2017 |
Curing Cancer with Machine Learning is Super Hard
|
Aug 14, 2017 |
KL Divergence
|
Aug 07, 2017 |
Sabermetrics
|
Jul 31, 2017 |
What Data Scientists Can Learn from Software Engineers
|
Jul 24, 2017 |
Software Engineering to Data Science
|
Jul 17, 2017 |
Re-Release: Fighting Cholera with Data, 1854
|
Jul 10, 2017 |
Re-Release: Data Mining Enron
|
Jul 02, 2017 |
Factorization Machines
|
Jun 26, 2017 |
Anscombe's Quartet
|
Jun 19, 2017 |
Traffic Metering Algorithms
|
Jun 12, 2017 |
Page Rank
|
Jun 05, 2017 |
Fractional Dimensions
|
May 29, 2017 |
Things You Learn When Building Models for Big Data
|
May 22, 2017 |
How to Find New Things to Learn
|
May 15, 2017 |
Federated Learning
|
May 08, 2017 |
Word2Vec
|
May 01, 2017 |
Feature Processing for Text Analytics
|
Apr 24, 2017 |
Education Analytics
|
Apr 17, 2017 |
A Technical Deep Dive on Stanley, the First Self-Driving Car
|
Apr 10, 2017 |
An Introduction to Stanley, the First Self-Driving Car
|
Apr 03, 2017 |
Feature Importance
|
Mar 27, 2017 |
Space Codes!
|
Mar 20, 2017 |
Finding (and Studying) Wikipedia Trolls
|
Mar 13, 2017 |
A Sprint Through What's New in Neural Networks
|
Mar 06, 2017 |
Stein's Paradox
|
Feb 27, 2017 |
Empirical Bayes
|
Feb 20, 2017 |
Endogenous Variables and Measuring Protest Effectiveness
|
Feb 13, 2017 |
Calibrated Models
|
Feb 06, 2017 |
Rock the ROC Curve
|
Jan 30, 2017 |
Ensemble Algorithms
|
Jan 23, 2017 |
How to evaluate a translation: BLEU scores
|
Jan 16, 2017 |
Zero Shot Translation
|
Jan 09, 2017 |
Google Neural Machine Translation
|
Jan 02, 2017 |
Data and the Future of Medicine : Interview with Precision Medicine Initiative researcher Matt Might
|
Dec 26, 2016 |
Special Crossover Episode: Partially Derivative interview with White House Data Scientist DJ Patil
|
Dec 18, 2016 |
How to Lose at Kaggle
|
Dec 12, 2016 |
Attacking Discrimination in Machine Learning
|
Dec 05, 2016 |
Recurrent Neural Nets
|
Nov 28, 2016 |
Stealing a PIN with signal processing and machine learning
|
Nov 21, 2016 |
Neural Net Cryptography
|
Nov 14, 2016 |
Deep Blue
|
Nov 07, 2016 |
Organizing Google's Datasets
|
Oct 31, 2016 |
Fighting Cancer with Data Science: Followup
|
Oct 24, 2016 |
The 19-year-old determining the US election
|
Oct 17, 2016 |
How to Steal a Model
|
Oct 09, 2016 |
Regularization
|
Oct 03, 2016 |
The Cold Start Problem
|
Sep 26, 2016 |
Open Source Software for Data Science
|
Sep 19, 2016 |
Scikit + Optimization = Scikit-Optimize
|
Sep 12, 2016 |
Two Cultures: Machine Learning and Statistics
|
Sep 05, 2016 |
Optimization Solutions
|
Aug 29, 2016 |
Optimization Problems
|
Aug 22, 2016 |
Multi-level modeling for understanding DEADLY RADIOACTIVE GAS
|
Aug 15, 2016 |
How Polls Got Brexit "Wrong"
|
Aug 08, 2016 |
Election Forecasting
|
Aug 01, 2016 |
Machine Learning for Genomics
|
Jul 25, 2016 |
Climate Modeling
|
Jul 18, 2016 |
Reinforcement Learning Gone Wrong
|
Jul 11, 2016 |
Reinforcement Learning for Artificial Intelligence
|
Jul 03, 2016 |
Differential Privacy: how to study people without being weird and gross
|
Jun 27, 2016 |
How the sausage gets made
|
Jun 20, 2016 |
SMOTE: makin' yourself some fake minority data
|
Jun 13, 2016 |
Conjoint Analysis: like AB testing, but on steroids
|
Jun 06, 2016 |
Traffic Metering Algorithms
|
May 30, 2016 |
Um Detector 2: The Dynamic Time Warp
|
May 23, 2016 |
Inside a Data Analysis: Fraud Hunting at Enron
|
May 16, 2016 |
What's the biggest #bigdata?
|
May 09, 2016 |
Data Contamination
|
May 02, 2016 |
Model Interpretation (and Trust Issues)
|
Apr 25, 2016 |
Updates! Political Science Fraud and AlphaGo
|
Apr 18, 2016 |
Ecological Inference and Simpson's Paradox
|
Apr 11, 2016 |
Discriminatory Algorithms
|
Apr 04, 2016 |
Recommendation Engines and Privacy
|
Mar 28, 2016 |
Neural nets play cops and robbers (AKA generative adverserial networks)
|
Mar 21, 2016 |
A Data Scientist's View of the Fight against Cancer
|
Mar 14, 2016 |
Congress Bots and DeepDrumpf
|
Mar 11, 2016 |
Multi - Armed Bandits
|
Mar 07, 2016 |
Experiments and Messy, Tricky Causality
|
Mar 04, 2016 |
Backpropagation
|
Feb 29, 2016 |
Text Analysis on the State Of The Union
|
Feb 26, 2016 |
Paradigms in Artificial Intelligence
|
Feb 22, 2016 |
Survival Analysis
|
Feb 19, 2016 |
Gravitational Waves
|
Feb 15, 2016 |
The Turing Test
|
Feb 12, 2016 |
Item Response Theory: how smart ARE you?
|
Feb 08, 2016 |
Go!
|
Feb 05, 2016 |
Great Social Networks in History
|
Feb 01, 2016 |
How Much to Pay a Spy (and a lil' more auctions)
|
Jan 29, 2016 |
Sold! Auctions (Part 2)
|
Jan 25, 2016 |
Going Once, Going Twice: Auctions (Part 1)
|
Jan 22, 2016 |
Chernoff Faces and Minard Maps
|
Jan 18, 2016 |
t-SNE: Reduce Your Dimensions, Keep Your Clusters
|
Jan 15, 2016 |
The [Expletive Deleted] Problem
|
Jan 11, 2016 |
Unlabeled Supervised Learning--whaaa?
|
Jan 08, 2016 |
Hacking Neural Nets
|
Jan 05, 2016 |
Zipf's Law
|
Dec 31, 2015 |
Indie Announcement
|
Dec 30, 2015 |
Portrait Beauty
|
Dec 27, 2015 |
The Cocktail Party Problem
|
Dec 18, 2015 |
A Criminally Short Introduction to Semi Supervised Learning
|
Dec 04, 2015 |
Thresholdout: Down with Overfitting
|
Nov 27, 2015 |
The State of Data Science
|
Nov 10, 2015 |
Data Science for Making the World a Better Place
|
Nov 06, 2015 |
Kalman Runners
|
Oct 29, 2015 |
Neural Net Inception
|
Oct 23, 2015 |
Benford's Law
|
Oct 16, 2015 |
Guinness
|
Oct 07, 2015 |
PFun with P Values
|
Sep 02, 2015 |
Watson
|
Aug 25, 2015 |
Bayesian Psychics
|
Aug 18, 2015 |
Troll Detection
|
Aug 07, 2015 |
Yiddish Translation
|
Aug 03, 2015 |
Modeling Particles in Atomic Bombs
|
Jul 06, 2015 |
Random Number Generation
|
Jun 19, 2015 |
Electoral Insights (Part 2)
|
Jun 09, 2015 |
Electoral Insights (Part 1)
|
Jun 05, 2015 |
Falsifying Data
|
Jun 01, 2015 |
Reporter Bot
|
May 20, 2015 |
Careers in Data Science
|
May 16, 2015 |
That's "Dr Katie" to You
|
May 14, 2015 |
Neural Nets (Part 2)
|
May 11, 2015 |
Neural Nets (Part 1)
|
May 01, 2015 |
Inferring Authorship (Part 2)
|
Apr 28, 2015 |
Inferring Authorship (Part 1)
|
Apr 16, 2015 |
Statistical Mistakes and the Challenger Disaster
|
Apr 06, 2015 |
Genetics and Um Detection (HMM Part 2)
|
Mar 25, 2015 |
Introducing Hidden Markov Models (HMM Part 1)
|
Mar 24, 2015 |
Monte Carlo For Physicists
|
Mar 12, 2015 |
Random Kanye
|
Mar 04, 2015 |
Lie Detectors
|
Feb 25, 2015 |
The Enron Dataset
|
Feb 09, 2015 |
Labels and Where To Find Them
|
Feb 04, 2015 |
Um Detector 1
|
Jan 23, 2015 |
Better Facial Recognition with Fisherfaces
|
Jan 07, 2015 |
Facial Recognition with Eigenfaces
|
Jan 07, 2015 |
Stats of World Series Streaks
|
Dec 17, 2014 |
Computers Try to Tell Jokes
|
Nov 26, 2014 |
How Outliers Helped Defeat Cholera
|
Nov 22, 2014 |
Hunting for the Higgs
|
Nov 16, 2014 |