Linear Digressions

289 Episodio

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

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

   Pubblicato: 28/10/2019
3. Kalman Runners

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

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

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

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

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

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

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

    Pubblicato: 25/8/2019
11. Data Shapley

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

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

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

    Pubblicato: 29/7/2019
15. Interleaving

    Pubblicato: 22/7/2019
16. Federated Learning

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

    Pubblicato: 7/7/2019
18. Deepfakes

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

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

    Pubblicato: 17/6/2019