Data Science at Home

268 Épisodes

1. Episode 46: why do machine learning models fail? (Part 2)

   Publié: 04/09/2018
2. Episode 45: why do machine learning models fail?

   Publié: 28/08/2018
3. Episode 44: The predictive power of metadata

   Publié: 21/08/2018
4. Episode 43: Applied Text Analysis with Python (interview with Rebecca Bilbro)

   Publié: 14/08/2018
5. Episode 42: Attacking deep learning models (rebroadcast)

   Publié: 07/08/2018
6. Episode 41: How can deep neural networks reason

   Publié: 31/07/2018
7. Episode 40: Deep learning and image compression

   Publié: 24/07/2018
8. Episode 39: What is L1-norm and L2-norm?

   Publié: 19/07/2018
9. Episode 38: Collective intelligence (Part 2)

   Publié: 17/07/2018
10. Episode 38: Collective intelligence (Part 1)

    Publié: 12/07/2018
11. Episode 37: Predicting the weather with deep learning

    Publié: 09/07/2018
12. Episode 36: The dangers of machine learning and medicine

    Publié: 03/07/2018
13. Episode 35: Attacking deep learning models

    Publié: 29/06/2018
14. Episode 34: Get ready for AI winter

    Publié: 22/06/2018
15. Episode 33: Decentralized Machine Learning and the proof-of-train

    Publié: 11/06/2018
16. Episode 32: I am back. I have been building fitchain

    Publié: 04/06/2018
17. Founder Interview – Francesco Gadaleta of Fitchain

    Publié: 24/05/2018
18. Episode 31: The End of Privacy

    Publié: 02/04/2018
19. Episode 30: Neural networks and genetic evolution: an unfeasible approach

    Publié: 21/11/2017
20. Episode 29: Fail your AI company in 9 steps

    Publié: 11/11/2017