O'Reilly Data Show Podcast

60 Episodo

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

   Publicado: 3/1/2019
2. Trends in data, machine learning, and AI

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

   Publicado: 6/12/2018
4. Building tools for enterprise data science

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

   Publicado: 8/11/2018
6. Machine learning on encrypted data

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

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

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

   Publicado: 13/9/2018
10. Building accessible tools for large-scale computation and machine learning

    Publicado: 30/8/2018
11. Simplifying machine learning lifecycle management

    Publicado: 16/8/2018
12. How privacy-preserving techniques can lead to more robust machine learning models

    Publicado: 2/8/2018
13. Specialized hardware for deep learning will unleash innovation

    Publicado: 19/7/2018
14. Data regulations and privacy discussions are still in the early stages

    Publicado: 5/7/2018
15. Managing risk in machine learning models

    Publicado: 21/6/2018
16. The real value of data requires a holistic view of the end-to-end data pipeline

    Publicado: 7/6/2018
17. The evolution of data science, data engineering, and AI

    Publicado: 24/5/2018
18. Companies in China are moving quickly to embrace AI technologies

    Publicado: 10/5/2018
19. Teaching and implementing data science and AI in the enterprise

    Publicado: 26/4/2018
20. The importance of transparency and user control in machine learning

    Publicado: 12/4/2018