O'Reilly Data Show Podcast

60 Episodio

1. In the age of AI, fundamental value resides in data

   Pubblicato: 03/01/2019
2. Trends in data, machine learning, and AI

   Pubblicato: 20/12/2018
3. Tools for generating deep neural networks with efficient network architectures

   Pubblicato: 06/12/2018
4. Building tools for enterprise data science

   Pubblicato: 21/11/2018
5. Lessons learned while helping enterprises adopt machine learning

   Pubblicato: 08/11/2018
6. Machine learning on encrypted data

   Pubblicato: 25/10/2018
7. How social science research can inform the design of AI systems

   Pubblicato: 11/10/2018
8. Why it’s hard to design fair machine learning models

   Pubblicato: 27/09/2018
9. Using machine learning to improve dialog flow in conversational applications

   Pubblicato: 13/09/2018
10. Building accessible tools for large-scale computation and machine learning

    Pubblicato: 30/08/2018
11. Simplifying machine learning lifecycle management

    Pubblicato: 16/08/2018
12. How privacy-preserving techniques can lead to more robust machine learning models

    Pubblicato: 02/08/2018
13. Specialized hardware for deep learning will unleash innovation

    Pubblicato: 19/07/2018
14. Data regulations and privacy discussions are still in the early stages

    Pubblicato: 05/07/2018
15. Managing risk in machine learning models

    Pubblicato: 21/06/2018
16. The real value of data requires a holistic view of the end-to-end data pipeline

    Pubblicato: 07/06/2018
17. The evolution of data science, data engineering, and AI

    Pubblicato: 24/05/2018
18. Companies in China are moving quickly to embrace AI technologies

    Pubblicato: 10/05/2018
19. Teaching and implementing data science and AI in the enterprise

    Pubblicato: 26/04/2018
20. The importance of transparency and user control in machine learning

    Pubblicato: 12/04/2018