Linear Digressions

289 Épisodes

1. Interview with Joel Grus

   Publié: 10/06/2019
2. Re - Release: Factorization Machines

   Publié: 03/06/2019
3. Re-release: Auto-generating websites with deep learning

   Publié: 27/05/2019
4. Advice to those trying to get a first job in data science

   Publié: 19/05/2019
5. Re - Release: Machine Learning Technical Debt

   Publié: 12/05/2019
6. Estimating Software Projects, and Why It's Hard

   Publié: 05/05/2019
7. The Black Hole Algorithm

   Publié: 29/04/2019
8. Structure in AI

   Publié: 21/04/2019
9. The Great Data Science Specialist vs. Generalist Debate

   Publié: 15/04/2019
10. Google X, and Taking Risks the Smart Way

    Publié: 08/04/2019
11. Statistical Significance in Hypothesis Testing

    Publié: 01/04/2019
12. The Language Model Too Dangerous to Release

    Publié: 25/03/2019
13. The cathedral and the bazaar

    Publié: 17/03/2019
14. AlphaStar

    Publié: 11/03/2019
15. Are machine learning engineers the new data scientists?

    Publié: 04/03/2019
16. Interview with Alex Radovic, particle physicist turned machine learning researcher

    Publié: 25/02/2019
17. K Nearest Neighbors

    Publié: 17/02/2019
18. Not every deep learning paper is great. Is that a problem?

    Publié: 11/02/2019
19. The Assumptions of Ordinary Least Squares

    Publié: 03/02/2019
20. Quantile Regression

    Publié: 28/01/2019