Linear Digressions

289 Episodes

1. Interview with Joel Grus

   Published: 6/10/2019
2. Re - Release: Factorization Machines

   Published: 6/3/2019
3. Re-release: Auto-generating websites with deep learning

   Published: 5/27/2019
4. Advice to those trying to get a first job in data science

   Published: 5/19/2019
5. Re - Release: Machine Learning Technical Debt

   Published: 5/12/2019
6. Estimating Software Projects, and Why It's Hard

   Published: 5/5/2019
7. The Black Hole Algorithm

   Published: 4/29/2019
8. Structure in AI

   Published: 4/21/2019
9. The Great Data Science Specialist vs. Generalist Debate

   Published: 4/15/2019
10. Google X, and Taking Risks the Smart Way

    Published: 4/8/2019
11. Statistical Significance in Hypothesis Testing

    Published: 4/1/2019
12. The Language Model Too Dangerous to Release

    Published: 3/25/2019
13. The cathedral and the bazaar

    Published: 3/17/2019
14. AlphaStar

    Published: 3/11/2019
15. Are machine learning engineers the new data scientists?

    Published: 3/4/2019
16. Interview with Alex Radovic, particle physicist turned machine learning researcher

    Published: 2/25/2019
17. K Nearest Neighbors

    Published: 2/17/2019
18. Not every deep learning paper is great. Is that a problem?

    Published: 2/11/2019
19. The Assumptions of Ordinary Least Squares

    Published: 2/3/2019
20. Quantile Regression

    Published: 1/28/2019