Adventures in Machine Learning

A podcast by Charles M Wood - Thursdays

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183 Episodes

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

    Published: 2/5/2021
  2. ML 020: How to Make an Impact on the Development Community

    Published: 2/2/2021
  3. ML 019: Artificial Intelligence as a Service with Peter Elger and Eóin Shanaghy

    Published: 1/26/2021
  4. ML 018: Mastering Data Pipelines with Apache Spark with Jean-Georges Perrin

    Published: 1/19/2021
  5. ML 017: The Nature of the World and AI with Rishal Hurbans

    Published: 1/12/2021
  6. ML 016: Python as a Basis for Machine Learning with Ken Youens-Clark

    Published: 1/5/2021
  7. BONUS: How to Crush Your Biggest Goals in 2021

    Published: 1/1/2021
  8. ML 015: Extracting Value from Data with Alexey Grigorev

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

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

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

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

    Published: 11/3/2020
  13. ML 011: History of AI in the UK with Laurence Moroney

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

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

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

    Published: 10/6/2020
  17. ML 007: Computer Vision & AI Scientist with Beril Sirmacek

    Published: 9/29/2020
  18. ML 006: Mad Science AI with Benson Ruan

    Published: 9/22/2020
  19. ML 005: Transfer Learning for NLP with Daniel Svoboda

    Published: 9/15/2020
  20. ML 004: Automated Machine Learning ML with Jorge Torres

    Published: 9/11/2020

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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.