Linear Digressions

289 Episodes

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

   Published: 11/4/2019
2. The Care and Feeding of Data Scientists: Becoming a Data Science Manager

   Published: 10/28/2019
3. Kalman Runners

   Published: 10/13/2019
4. What's *really* so hard about feature engineering?

   Published: 10/6/2019
5. Data storage for analytics: stars and snowflakes

   Published: 9/30/2019
6. Data storage: transactions vs. analytics

   Published: 9/23/2019
7. GROVER: an algorithm for making, and detecting, fake news

   Published: 9/16/2019
8. Data science teams as innovation initiatives

   Published: 9/9/2019
9. Can Fancy Running Shoes Cause You To Run Faster?

   Published: 9/1/2019
10. Organizational Models for Data Scientists

    Published: 8/25/2019
11. Data Shapley

    Published: 8/19/2019
12. A Technical Deep Dive on Stanley, the First Self-Driving Car

    Published: 8/12/2019
13. An Introduction to Stanley, the First Self-Driving Car

    Published: 8/5/2019
14. Putting the "science" in data science: the scientific method, the null hypothesis, and p-hacking

    Published: 7/29/2019
15. Interleaving

    Published: 7/22/2019
16. Federated Learning

    Published: 7/14/2019
17. Endogenous Variables and Measuring Protest Effectiveness

    Published: 7/7/2019
18. Deepfakes

    Published: 7/1/2019
19. Revisiting Biased Word Embeddings

    Published: 6/24/2019
20. Attention in Neural Nets

    Published: 6/17/2019