Talking Machines

En podcast av Tote Bag Productions

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110 Avsnitt

  1. The Long View and Learning in Person

    Publicerades: 2017-09-21
  2. Machine Learning in the Field and Bayesian Baked Goods

    Publicerades: 2017-09-08
  3. Data Science Africa with Dina Machuve

    Publicerades: 2017-08-10
  4. The Church of Bayes and Collecting Data

    Publicerades: 2017-07-28
  5. Getting a Start in ML and Applied AI at Facebook

    Publicerades: 2017-07-13
  6. Bias Variance Dilemma for Humans and the Arm Farm

    Publicerades: 2017-06-29
  7. Overfitting and Asking Ecological Questions with ML

    Publicerades: 2017-06-15
  8. Graphons and "Inferencing"

    Publicerades: 2017-05-25
  9. Hosts of Talking Machines: Neil Lawrence and Ryan Adams

    Publicerades: 2017-04-27
  10. ANGLICAN and Probabilistic Programming

    Publicerades: 2016-09-01
  11. Eric Lander and Restricted Boltzmann Machines

    Publicerades: 2016-08-18
  12. Generative Art and Hamiltonian Monte Carlo

    Publicerades: 2016-08-04
  13. Perturb-and-MAP and Machine Learning in the Flint Water Crisis

    Publicerades: 2016-07-21
  14. Automatic Translation and t-SNE

    Publicerades: 2016-07-07
  15. Fantasizing Cats and Data Numbers

    Publicerades: 2016-06-16
  16. Spark and ICML

    Publicerades: 2016-06-02
  17. Computational Learning Theory and Machine Learning for Understanding Cells

    Publicerades: 2016-05-19
  18. Sparse Coding and MADBITS

    Publicerades: 2016-05-05
  19. Remembering David MacKay

    Publicerades: 2016-04-21
  20. Machine Learning and Society

    Publicerades: 2016-04-08

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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