O'Reilly Data Show Podcast

60 Folgen

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

   Vom: 3.1.2019
2. Trends in data, machine learning, and AI

   Vom: 20.12.2018
3. Tools for generating deep neural networks with efficient network architectures

   Vom: 6.12.2018
4. Building tools for enterprise data science

   Vom: 21.11.2018
5. Lessons learned while helping enterprises adopt machine learning

   Vom: 8.11.2018
6. Machine learning on encrypted data

   Vom: 25.10.2018
7. How social science research can inform the design of AI systems

   Vom: 11.10.2018
8. Why it’s hard to design fair machine learning models

   Vom: 27.9.2018
9. Using machine learning to improve dialog flow in conversational applications

   Vom: 13.9.2018
10. Building accessible tools for large-scale computation and machine learning

    Vom: 30.8.2018
11. Simplifying machine learning lifecycle management

    Vom: 16.8.2018
12. How privacy-preserving techniques can lead to more robust machine learning models

    Vom: 2.8.2018
13. Specialized hardware for deep learning will unleash innovation

    Vom: 19.7.2018
14. Data regulations and privacy discussions are still in the early stages

    Vom: 5.7.2018
15. Managing risk in machine learning models

    Vom: 21.6.2018
16. The real value of data requires a holistic view of the end-to-end data pipeline

    Vom: 7.6.2018
17. The evolution of data science, data engineering, and AI

    Vom: 24.5.2018
18. Companies in China are moving quickly to embrace AI technologies

    Vom: 10.5.2018
19. Teaching and implementing data science and AI in the enterprise

    Vom: 26.4.2018
20. The importance of transparency and user control in machine learning

    Vom: 12.4.2018