Linear Digressions

A podcast by Ben Jaffe and Katie Malone

Categories:

289 Episodes

  1. Google Flu Trends

    Published: 26/03/2018
  2. How to pick projects for a professional data science team

    Published: 19/03/2018
  3. Autoencoders

    Published: 12/03/2018
  4. When Private Data Isn't Private Anymore

    Published: 05/03/2018
  5. What makes a machine learning algorithm "superhuman"?

    Published: 26/02/2018
  6. Open Data and Open Science

    Published: 19/02/2018
  7. Defining the quality of a machine learning production system

    Published: 12/02/2018
  8. Auto-generating websites with deep learning

    Published: 04/02/2018
  9. The Case for Learned Index Structures, Part 2: Hash Maps and Bloom Filters

    Published: 29/01/2018
  10. The Case for Learned Index Structures, Part 1: B-Trees

    Published: 22/01/2018
  11. Challenges with Using Machine Learning to Classify Chest X-Rays

    Published: 15/01/2018
  12. The Fourier Transform

    Published: 08/01/2018
  13. Statistics of Beer

    Published: 02/01/2018
  14. Re - Release: Random Kanye

    Published: 24/12/2017
  15. Debiasing Word Embeddings

    Published: 18/12/2017
  16. The Kernel Trick and Support Vector Machines

    Published: 11/12/2017
  17. Maximal Margin Classifiers

    Published: 04/12/2017
  18. Re - Release: The Cocktail Party Problem

    Published: 27/11/2017
  19. Clustering with DBSCAN

    Published: 20/11/2017
  20. The Kaggle Survey on Data Science

    Published: 13/11/2017

7 / 15

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