Linear Digressions

A podcast by Ben Jaffe and Katie Malone

Categorie:

289 Episodio

  1. Anscombe's Quartet

    Pubblicato: 19/6/2017
  2. Traffic Metering Algorithms

    Pubblicato: 12/6/2017
  3. Page Rank

    Pubblicato: 5/6/2017
  4. Fractional Dimensions

    Pubblicato: 29/5/2017
  5. Things You Learn When Building Models for Big Data

    Pubblicato: 22/5/2017
  6. How to Find New Things to Learn

    Pubblicato: 15/5/2017
  7. Federated Learning

    Pubblicato: 8/5/2017
  8. Word2Vec

    Pubblicato: 1/5/2017
  9. Feature Processing for Text Analytics

    Pubblicato: 24/4/2017
  10. Education Analytics

    Pubblicato: 17/4/2017
  11. A Technical Deep Dive on Stanley, the First Self-Driving Car

    Pubblicato: 10/4/2017
  12. An Introduction to Stanley, the First Self-Driving Car

    Pubblicato: 3/4/2017
  13. Feature Importance

    Pubblicato: 27/3/2017
  14. Space Codes!

    Pubblicato: 20/3/2017
  15. Finding (and Studying) Wikipedia Trolls

    Pubblicato: 13/3/2017
  16. A Sprint Through What's New in Neural Networks

    Pubblicato: 6/3/2017
  17. Empirical Bayes

    Pubblicato: 20/2/2017
  18. Endogenous Variables and Measuring Protest Effectiveness

    Pubblicato: 13/2/2017
  19. Calibrated Models

    Pubblicato: 6/2/2017
  20. Ensemble Algorithms

    Pubblicato: 23/1/2017

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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