Data Science at Home

264 Folgen

1. Rust and machine learning #1 (Ep. 107)

   Vom: 17.6.2020
2. Protecting workers with artificial intelligence (with Sandeep Pandya CEO Everguard.ai)(Ep. 106)

   Vom: 15.6.2020
3. Compressing deep learning models: rewinding (Ep.105)

   Vom: 1.6.2020
4. Compressing deep learning models: distillation (Ep.104)

   Vom: 20.5.2020
5. Pandemics and the risks of collecting data (Ep. 103)

   Vom: 8.5.2020
6. Why average can get your predictions very wrong (ep. 102)

   Vom: 19.4.2020
7. Activate deep learning neurons faster with Dynamic RELU (ep. 101)

   Vom: 1.4.2020
8. WARNING!! Neural networks can memorize secrets (ep. 100)

   Vom: 23.3.2020
9. Attacks to machine learning model: inferring ownership of training data (Ep. 99)

   Vom: 14.3.2020
10. Don't be naive with data anonymization (Ep. 98)

    Vom: 8.3.2020
11. Why sharing real data is dangerous (Ep. 97)

    Vom: 1.3.2020
12. Building reproducible machine learning in production (Ep. 96)

    Vom: 22.2.2020
13. Bridging the gap between data science and data engineering: metrics (Ep. 95)

    Vom: 14.2.2020
14. A big welcome to Pryml: faster machine learning applications to production

    Vom: 7.2.2020
15. It's cold outside. Let's speak about AI winter (Ep. 93)

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

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

    Vom: 23.12.2019
18. The dark side of AI: recommend and manipulate (Ep. 90)

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

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

    Vom: 18.11.2019