Linear Digressions

En podcast af Ben Jaffe and Katie Malone

Kategorier:

289 Episoder

  1. Interview with Joel Grus

    Udgivet: 10.6.2019
  2. Re - Release: Factorization Machines

    Udgivet: 3.6.2019
  3. Re-release: Auto-generating websites with deep learning

    Udgivet: 27.5.2019
  4. Advice to those trying to get a first job in data science

    Udgivet: 19.5.2019
  5. Re - Release: Machine Learning Technical Debt

    Udgivet: 12.5.2019
  6. Estimating Software Projects, and Why It's Hard

    Udgivet: 5.5.2019
  7. The Black Hole Algorithm

    Udgivet: 29.4.2019
  8. Structure in AI

    Udgivet: 21.4.2019
  9. The Great Data Science Specialist vs. Generalist Debate

    Udgivet: 15.4.2019
  10. Google X, and Taking Risks the Smart Way

    Udgivet: 8.4.2019
  11. Statistical Significance in Hypothesis Testing

    Udgivet: 1.4.2019
  12. The Language Model Too Dangerous to Release

    Udgivet: 25.3.2019
  13. The cathedral and the bazaar

    Udgivet: 17.3.2019
  14. AlphaStar

    Udgivet: 11.3.2019
  15. Are machine learning engineers the new data scientists?

    Udgivet: 4.3.2019
  16. Interview with Alex Radovic, particle physicist turned machine learning researcher

    Udgivet: 25.2.2019
  17. K Nearest Neighbors

    Udgivet: 17.2.2019
  18. Not every deep learning paper is great. Is that a problem?

    Udgivet: 11.2.2019
  19. The Assumptions of Ordinary Least Squares

    Udgivet: 3.2.2019
  20. Quantile Regression

    Udgivet: 28.1.2019

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In each episode, your hosts explore machine learning and data science through interesting (and often very unusual) applications.

Visit the podcast's native language site