Talking Machines

A podcast by Tote Bag Productions

Categorie:

110 Episodio

  1. What Does Red Sound Like

    Pubblicato: 30/08/2019
  2. Not What But Why

    Pubblicato: 15/08/2019
  3. Idea Pandemics and Workshop Walkthrough

    Pubblicato: 01/08/2019
  4. PosterSession.ai and Deep Quaggles

    Pubblicato: 18/07/2019
  5. The View from Addis Ababa

    Pubblicato: 04/07/2019
  6. DSA Addis Ababa and ICML Los Angeles

    Pubblicato: 21/06/2019
  7. Data Trusts and Citation Trends

    Pubblicato: 06/06/2019
  8. Reproducibly and Revisiting History

    Pubblicato: 23/05/2019
  9. Insights from AISTATS

    Pubblicato: 10/05/2019
  10. The Deep End of Deep Learning

    Pubblicato: 25/04/2019
  11. Exploring MARS and Getting back to Bayesics

    Pubblicato: 11/04/2019
  12. The Sweetness of a Bitter Lesson and Bringing ML and Healthcare Closer

    Pubblicato: 28/03/2019
  13. Slowed Down Conferences and Even More Summer Schools

    Pubblicato: 14/03/2019
  14. Jupyter Notebooks and Modern Model Distribution

    Pubblicato: 28/02/2019
  15. Real World Real Time and Five Papers for Mike Tipping

    Pubblicato: 15/02/2019
  16. The Bezos Paradox and Machine Learning Languages

    Pubblicato: 01/02/2019
  17. Being Global Bit by Bit

    Pubblicato: 17/01/2019
  18. The Possibility Of Explanation and The End of Season Four

    Pubblicato: 29/11/2018
  19. Neural Information Processing Systems and Distributed Internal Intelligence Systems

    Pubblicato: 16/11/2018
  20. Data Driven Ideas and Actionable Privacy

    Pubblicato: 01/11/2018

2 / 6

Talking Machines is your window into the world of machine learning. Your hosts, Katherine Gorman and Neil Lawrence, bring you clear conversations with experts in the field, insightful discussions of industry news, and useful answers to your questions. Machine learning is changing the questions we can ask of the world around us, here we explore how to ask the best questions and what to do with the answers. Hosted on Acast. See acast.com/privacy for more information.

Visit the podcast's native language site