Data Science at Home

Podcast autorstwa Francesco Gadaleta

Kategorie:

268 Odcinki

  1. The dark side of AI: metadata and the death of privacy (Ep. 91)

    Opublikowany: 23.12.2019
  2. The dark side of AI: recommend and manipulate (Ep. 90)

    Opublikowany: 11.12.2019
  3. The dark side of AI: social media and the optimization of addiction (Ep. 89)

    Opublikowany: 3.12.2019
  4. How to improve the stability of training a GAN (Ep. 88)

    Opublikowany: 18.11.2019
  5. What if I train a neural network with random data? (with Stanisław Jastrzębski) (Ep. 87)

    Opublikowany: 12.11.2019
  6. Deeplearning is easier when it is illustrated (with Jon Krohn) (Ep. 86)

    Opublikowany: 5.11.2019
  7. More powerful deep learning with transformers (Ep. 84)

    Opublikowany: 27.10.2019
  8. What is wrong with reinforcement learning? (Ep. 82)

    Opublikowany: 15.10.2019
  9. Have you met Shannon? Conversation with Jimmy Soni and Rob Goodman about one of the greatest minds in history (Ep. 81)

    Opublikowany: 10.10.2019
  10. Attacking machine learning for fun and profit (with the authors of SecML Ep. 80)

    Opublikowany: 1.10.2019
  11. [RB] How to scale AI in your organisation (Ep. 79)

    Opublikowany: 26.09.2019
  12. Replicating GPT-2, the most dangerous NLP model (with Aaron Gokaslan) (Ep. 78)

    Opublikowany: 23.09.2019
  13. How to generate very large images with GANs (Ep. 76)

    Opublikowany: 6.09.2019
  14. How to cluster tabular data with Markov Clustering (Ep. 73)

    Opublikowany: 20.08.2019
  15. Waterfall or Agile? The best methodology for AI and machine learning (Ep. 72)

    Opublikowany: 14.08.2019
  16. Training neural networks faster without GPU (Ep. 71)

    Opublikowany: 6.08.2019
  17. Validate neural networks without data with Dr. Charles Martin (Ep. 70)

    Opublikowany: 23.07.2019
  18. Complex video analysis made easy with Videoflow (Ep. 69)

    Opublikowany: 16.07.2019
  19. Episode 68: AI and the future of banking with Chris Skinner [RB]

    Opublikowany: 9.07.2019
  20. Episode 67: Classic Computer Science Problems in Python

    Opublikowany: 2.07.2019

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