Data Science at Home

Podcast tekijän mukaan Francesco Gadaleta

Kategoriat:

268 Jaksot

  1. What happens to data transfer after Schrems II? (Ep. 131)

    Julkaistiin: 4.12.2020
  2. Test-First Machine Learning [RB] (Ep. 130)

    Julkaistiin: 1.12.2020
  3. Similarity in Machine Learning (Ep. 129)

    Julkaistiin: 24.11.2020
  4. Distill data and train faster, better, cheaper (Ep. 128)

    Julkaistiin: 17.11.2020
  5. Machine Learning in Rust: Amadeus with Alec Mocatta [RB] (ep. 127)

    Julkaistiin: 11.11.2020
  6. Top-3 ways to put machine learning models into production (Ep. 126)

    Julkaistiin: 7.11.2020
  7. Remove noise from data with deep learning (Ep.125)

    Julkaistiin: 3.11.2020
  8. What is contrastive learning and why it is so powerful? (Ep. 124)

    Julkaistiin: 30.10.2020
  9. Neural search (Ep. 123)

    Julkaistiin: 23.10.2020
  10. Let's talk about federated learning (Ep. 122)

    Julkaistiin: 18.10.2020
  11. How to test machine learning in production (Ep. 121)

    Julkaistiin: 11.10.2020
  12. Why synthetic data cannot boost machine learning (Ep. 120)

    Julkaistiin: 26.9.2020
  13. Machine learning in production: best practices [LIVE from twitch.tv]

    Julkaistiin: 16.9.2020
  14. Testing in machine learning: checking deeplearning models (Ep. 118)

    Julkaistiin: 4.9.2020
  15. Testing in machine learning: generating tests and data (Ep. 117)

    Julkaistiin: 29.8.2020
  16. Why you care about homomorphic encryption (Ep. 116)

    Julkaistiin: 12.8.2020
  17. Test-First machine learning (Ep. 115)

    Julkaistiin: 3.8.2020
  18. GPT-3 cannot code (and never will) (Ep. 114)

    Julkaistiin: 26.7.2020
  19. Make Stochastic Gradient Descent Fast Again (Ep. 113)

    Julkaistiin: 22.7.2020
  20. What data transformation library should I use? Pandas vs Dask vs Ray vs Modin vs Rapids (Ep. 112)

    Julkaistiin: 19.7.2020

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