Linear Digressions

289 Episodes

1. Google Flu Trends

   Published: 3/26/2018
2. How to pick projects for a professional data science team

   Published: 3/19/2018
3. Autoencoders

   Published: 3/12/2018
4. When Private Data Isn't Private Anymore

   Published: 3/5/2018
5. What makes a machine learning algorithm "superhuman"?

   Published: 2/26/2018
6. Open Data and Open Science

   Published: 2/19/2018
7. Defining the quality of a machine learning production system

   Published: 2/12/2018
8. Auto-generating websites with deep learning

   Published: 2/4/2018
9. The Case for Learned Index Structures, Part 2: Hash Maps and Bloom Filters

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

    Published: 1/22/2018
11. Challenges with Using Machine Learning to Classify Chest X-Rays

    Published: 1/15/2018
12. The Fourier Transform

    Published: 1/8/2018
13. Statistics of Beer

    Published: 1/2/2018
14. Re - Release: Random Kanye

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

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

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

    Published: 12/4/2017
18. Re - Release: The Cocktail Party Problem

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

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

    Published: 11/13/2017