Data Science at Home

268 Episodes

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

   Published: 12/23/2019
2. The dark side of AI: recommend and manipulate (Ep. 90)

   Published: 12/11/2019
3. The dark side of AI: social media and the optimization of addiction (Ep. 89)

   Published: 12/3/2019
4. How to improve the stability of training a GAN (Ep. 88)

   Published: 11/18/2019
5. What if I train a neural network with random data? (with Stanisław Jastrzębski) (Ep. 87)

   Published: 11/12/2019
6. Deeplearning is easier when it is illustrated (with Jon Krohn) (Ep. 86)

   Published: 11/5/2019
7. More powerful deep learning with transformers (Ep. 84)

   Published: 10/27/2019
8. What is wrong with reinforcement learning? (Ep. 82)

   Published: 10/15/2019
9. Have you met Shannon? Conversation with Jimmy Soni and Rob Goodman about one of the greatest minds in history (Ep. 81)

   Published: 10/10/2019
10. Attacking machine learning for fun and profit (with the authors of SecML Ep. 80)

    Published: 10/1/2019
11. [RB] How to scale AI in your organisation (Ep. 79)

    Published: 9/26/2019
12. Replicating GPT-2, the most dangerous NLP model (with Aaron Gokaslan) (Ep. 78)

    Published: 9/23/2019
13. How to generate very large images with GANs (Ep. 76)

    Published: 9/6/2019
14. How to cluster tabular data with Markov Clustering (Ep. 73)

    Published: 8/20/2019
15. Waterfall or Agile? The best methodology for AI and machine learning (Ep. 72)

    Published: 8/14/2019
16. Training neural networks faster without GPU (Ep. 71)

    Published: 8/6/2019
17. Validate neural networks without data with Dr. Charles Martin (Ep. 70)

    Published: 7/23/2019
18. Complex video analysis made easy with Videoflow (Ep. 69)

    Published: 7/16/2019
19. Episode 68: AI and the future of banking with Chris Skinner [RB]

    Published: 7/9/2019
20. Episode 67: Classic Computer Science Problems in Python

    Published: 7/2/2019