120 Episoade

  1. Joaquin Candela — Definitions of Fairness

    Publicat: 01.10.2020
  2. Richard Socher — The Challenges of Making ML Work in the Real World

    Publicat: 29.09.2020
  3. Zack Chase Lipton — The Medical Machine Learning Landscape

    Publicat: 17.09.2020
  4. Anthony Goldbloom — How to Win Kaggle Competitions

    Publicat: 09.09.2020
  5. Suzana Ilić — Cultivating Machine Learning Communities

    Publicat: 02.09.2020
  6. Jeremy Howard — The Story of fast.ai and Why Python Is Not the Future of ML

    Publicat: 25.08.2020
  7. Anantha Kancherla — Building Level 5 Autonomous Vehicles

    Publicat: 12.08.2020
  8. Bharath Ramsundar — Deep Learning for Molecules and Medicine Discovery

    Publicat: 05.08.2020
  9. Chip Huyen — ML Research and Production Pipelines

    Publicat: 29.07.2020
  10. Peter Skomoroch — Product Management for AI

    Publicat: 22.07.2020
  11. Josh Tobin — Productionizing ML Models

    Publicat: 08.07.2020
  12. Miles Brundage — Societal Impacts of Artificial Intelligence

    Publicat: 01.07.2020
  13. Hamel Husain — Building Machine Learning Tools

    Publicat: 24.06.2020
  14. Peter Welinder — Deep Reinforcement Learning and Robotics

    Publicat: 17.06.2020
  15. Vicki Boykis — Machine Learning Across Industries

    Publicat: 04.06.2020
  16. Angela & Danielle — Designing ML Models for Millions of Consumer Robots

    Publicat: 06.05.2020
  17. Jack Clark — Building Trustworthy AI Systems

    Publicat: 22.04.2020
  18. Rachael Tatman — Conversational AI and Linguistics

    Publicat: 07.04.2020
  19. Nicolas Koumchatzky — Machine Learning in Production for Self-Driving Cars

    Publicat: 21.03.2020
  20. Brandon Rohrer — Machine Learning in Production for Robots

    Publicat: 11.03.2020

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Join Lukas Biewald on Gradient Dissent, an AI-focused podcast brought to you by Weights & Biases. Dive into fascinating conversations with industry giants from NVIDIA, Meta, Google, Lyft, OpenAI, and more. Explore the cutting-edge of AI and learn the intricacies of bringing models into production.

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