Linear Digressions

So long, and thanks for all the fish

A Reality Check on AI-Driven Medical Assistants

A Data Science Take on Open Policing Data

Procella: YouTube's super-system for analytics data storage

The Data Science Open Source Ecosystem

Rock the ROC Curve

Criminology and Data Science

Racism, the criminal justice system, and data science

An interstitial word from Ben

Convolutional Neural Networks

Stein's Paradox

Protecting Individual-Level Census Data with Differential Privacy

Causal Trees

The Grammar Of Graphics

Gaussian Processes

Keeping ourselves honest when we work with observational healthcare data

Changing our formulation of AI to avoid runaway risks: Interview with Prof. Stuart Russell

Putting machine learning into a database

The work-from-home episode

Understanding Covid-19 transmission: what the data suggests about how the disease spreads

Network effects re-release: when the power of a public health measure lies in widespread adoption

Causal inference when you can't experiment: difference-in-differences and synthetic controls

Better know a distribution: the Poisson distribution

The Lottery Ticket Hypothesis

Interesting technical issues prompted by GDPR and data privacy concerns

Thinking of data science initiatives as innovation initiatives

Building a curriculum for educating data scientists: Interview with Prof. Xiao-Li Meng

Running experiments when there are network effects

Zeroing in on what makes adversarial examples possible

Unsupervised Dimensionality Reduction: UMAP vs t-SNE

Data scientists: beware of simple metrics

Communicating data science, from academia to industry

Optimizing for the short-term vs. the long-term

Interview with Prof. Andrew Lo, on using data science to inform complex business decisions

Using machine learning to predict drug approvals

Facial recognition, society, and the law

Lessons learned from doing data science, at scale, in industry

Varsity A/B Testing

The Care and Feeding of Data Scientists: Growing Careers

The Care and Feeding of Data Scientists: Recruiting and Hiring Data Scientists

The Care and Feeding of Data Scientists: Becoming a Data Science Manager

Procella: YouTube's super-system for analytics data storage

Kalman Runners

What's *really* so hard about feature engineering?

Data storage for analytics: stars and snowflakes

Data storage: transactions vs. analytics

GROVER: an algorithm for making, and detecting, fake news

Data science teams as innovation initiatives

Can Fancy Running Shoes Cause You To Run Faster?

Organizational Models for Data Scientists