Adventures in Machine Learning

Un podcast de Charles M Wood - Les jeudis

Les jeudis

Catégories:

183 Épisodes

  1. BONUS: Measuring Apps and Entrepreneurship with John-Daniel Trask

    Publié: 05/02/2021
  2. ML 020: How to Make an Impact on the Development Community

    Publié: 02/02/2021
  3. ML 019: Artificial Intelligence as a Service with Peter Elger and Eóin Shanaghy

    Publié: 26/01/2021
  4. ML 018: Mastering Data Pipelines with Apache Spark with Jean-Georges Perrin

    Publié: 19/01/2021
  5. ML 017: The Nature of the World and AI with Rishal Hurbans

    Publié: 12/01/2021
  6. ML 016: Python as a Basis for Machine Learning with Ken Youens-Clark

    Publié: 05/01/2021
  7. BONUS: How to Crush Your Biggest Goals in 2021

    Publié: 01/01/2021
  8. ML 015: Extracting Value from Data with Alexey Grigorev

    Publié: 29/12/2020
  9. ML 014: Deep Learning with Structured Data with Mark Ryan

    Publié: 23/12/2020
  10. BONUS: How to do LARGE Volumes of HIGH Quality Work - While Spending Fewer Hours Working

    Publié: 27/11/2020
  11. ML 013: Recommender Systems with Frank Kane

    Publié: 17/11/2020
  12. ML 012: Machine Learning for Mere Mortals with Nick Chase

    Publié: 03/11/2020
  13. ML 011: History of AI in the UK with Laurence Moroney

    Publié: 27/10/2020
  14. ML 010: Brains, Guitars, and JavaScript with Milecia McGregor

    Publié: 20/10/2020
  15. ML 009: Effective Machine Learning in Academia and Industry with Hassan Kane

    Publié: 13/10/2020
  16. ML 008: TensorFlow.js and YOU with Jason Mayes

    Publié: 06/10/2020
  17. ML 007: Computer Vision & AI Scientist with Beril Sirmacek

    Publié: 29/09/2020
  18. ML 006: Mad Science AI with Benson Ruan

    Publié: 22/09/2020
  19. ML 005: Transfer Learning for NLP with Daniel Svoboda

    Publié: 15/09/2020
  20. ML 004: Automated Machine Learning ML with Jorge Torres

    Publié: 11/09/2020

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Machine Learning is growing in leaps and bounds both in capability and adoption. Listen to our experts discuss the ideas and fundamentals needed to succeed as a Machine Learning Engineer.Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.

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