Data Science at Home

263 Odcinki

1. Protecting workers with artificial intelligence (with Sandeep Pandya CEO Everguard.ai)(Ep. 106)

   Opublikowany: 15.06.2020
2. Compressing deep learning models: rewinding (Ep.105)

   Opublikowany: 1.06.2020
3. Compressing deep learning models: distillation (Ep.104)

   Opublikowany: 20.05.2020
4. Pandemics and the risks of collecting data (Ep. 103)

   Opublikowany: 8.05.2020
5. Why average can get your predictions very wrong (ep. 102)

   Opublikowany: 19.04.2020
6. Activate deep learning neurons faster with Dynamic RELU (ep. 101)

   Opublikowany: 1.04.2020
7. WARNING!! Neural networks can memorize secrets (ep. 100)

   Opublikowany: 23.03.2020
8. Attacks to machine learning model: inferring ownership of training data (Ep. 99)

   Opublikowany: 14.03.2020
9. Don't be naive with data anonymization (Ep. 98)

   Opublikowany: 8.03.2020
10. Why sharing real data is dangerous (Ep. 97)

    Opublikowany: 1.03.2020
11. Building reproducible machine learning in production (Ep. 96)

    Opublikowany: 22.02.2020
12. Bridging the gap between data science and data engineering: metrics (Ep. 95)

    Opublikowany: 14.02.2020
13. A big welcome to Pryml: faster machine learning applications to production

    Opublikowany: 7.02.2020
14. It's cold outside. Let's speak about AI winter (Ep. 93)

    Opublikowany: 31.12.2019
15. The dark side of AI: bias in the machine (Ep. 92)

    Opublikowany: 28.12.2019
16. The dark side of AI: metadata and the death of privacy (Ep. 91)

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

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

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

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

    Opublikowany: 12.11.2019