Practical AI: Machine Learning, Data Science

By Changelog Media

Making artificial intelligence practical, productive, and accessible to everyone. Practical AI is a show in which technology professionals, business people, students, enthusiasts, and expert guests engage in lively discussions about Artificial Intelligence and related topics (Machine Learning, Deep Learning, Neural Networks, etc). The focus is on productive implementations and real-world scenarios that are accessible to everyone. If you want to keep up with the latest advances in AI, while keeping one foot in the real world, then this is the show for you!

  1. 1.
    AI is creating never before heard sounds! 🎵
    45:03
  2. 2.
    Building a data team
    45:40
  3. 3.
    Towards stability and robustness
    48:31
  4. 4.
    From symbols to AI pair programmers 💻
    48:37
  5. 5.
    Vector databases for machine learning
    42:36
  6. 6.
    Multi-GPU training is hard (without PyTorch Lightning)
    46:25
  7. 7.
    Learning to learn deep learning 📖
    43:50
  8. 8.
    The fastest way to build ML-powered apps
    43:13
  1. 9.
    Elixir meets machine learning
    1:01:53
  2. 10.
    Apache TVM and OctoML
    49:06
  3. 11.
    25 years of speech technology innovation
    42:40
  4. 12.
    Generating "hunches" using smart home data 🏠
    42:42
  5. 13.
    Mapping the world
    53:10
  6. 14.
    Data science for intuitive user experiences
    52:58
  7. 15.
    Going full bore with Graphcore!
    44:28
  8. 16.
    Next-gen voice assistants
    50:48
  9. 17.
    Women in Data Science (WiDS)
    56:46
  10. 18.
    Recommender systems and high-frequency trading
    43:22
  11. 19.
    Deep learning technology for drug discovery
    57:11
  12. 20.
    Green AI 🌲
    1:00:12
  13. 21.
    Low code, no code, accelerated code, & failing code
    48:20
  14. 22.
    The AI doc will see you now
    46:05
  15. 23.
    Cooking up synthetic data with Gretel
    47:36
  16. 24.
    The nose knows
    54:58
  17. 25.
    Accelerating ML innovation at MLCommons
    51:10
  18. 26.
    The $1 trillion dollar ML model 💵
    48:40
  19. 27.
    Getting in the Flow with Snorkel AI
    46:56
  20. 28.
    Engaging with governments on AI for good
    25:34
  21. 29.
    From research to product at Azure AI
    49:00
  22. 30.
    The world's largest open library dataset
    43:58
  23. 31.
    A casual conversation concerning causal inference
    51:27
  24. 32.
    Building a deep learning workstation
    49:27
  25. 33.
    Killer developer tools for machine learning
    50:40
  26. 34.
    Reinforcement Learning for search
    47:03
  27. 35.
    When data leakage turns into a flood of trouble
    48:27
  28. 36.
    Productionizing AI at LinkedIn
    55:00
  29. 37.
    R, Data Science, & Computational Biology
    54:08
  30. 38.
    Learning about (Deep) Learning
    53:17
  31. 39.
    When AI goes wrong
    58:48
  32. 40.
    Speech tech and Common Voice at Mozilla
    58:30
  33. 41.
    Getting Waymo into autonomous driving
    1:00:35
  34. 42.
    Hidden Door and so much more
    56:03
  35. 43.
    Building the world's most popular data science platform
    59:12
  36. 44.
    Practical AI turns 100!!! 🎉
    1:09:53
  37. 45.
    Attack of the C̶l̶o̶n̶e̶s̶ Text!
    48:00
  38. 46.
    🤗 All things transformers with Hugging Face
    46:43
  39. 47.
    MLOps and tracking experiments with Allegro AI
    51:08
  40. 48.
    Practical AI Ethics
    52:30
  41. 49.
    The ins and outs of open source for AI
    47:17
  42. 50.
    Operationalizing ML/AI with MemSQL
    54:04

Listen to Practical AI: Machine Learning, Data Science now.

Listen to Practical AI: Machine Learning, Data Science in full in the Spotify app