O'Reilly Data Show Podcast

60 Folgen

1. Machine learning for operational analytics and business intelligence

   Vom: 10.10.2019
2. Machine learning and analytics for time series data

   Vom: 26.9.2019
3. Understanding deep neural networks

   Vom: 12.9.2019
4. Becoming a machine learning practitioner

   Vom: 29.8.2019
5. Labeling, transforming, and structuring training data sets for machine learning

   Vom: 15.8.2019
6. Make data science more useful

   Vom: 1.8.2019
7. Acquiring and sharing high-quality data

   Vom: 18.7.2019
8. Tools for machine learning development

   Vom: 3.7.2019
9. Enabling end-to-end machine learning pipelines in real-world applications

   Vom: 20.6.2019
10. Bringing scalable real-time analytics to the enterprise

    Vom: 9.6.2019
11. Applications of data science and machine learning in financial services

    Vom: 23.5.2019
12. Real-time entity resolution made accessible

    Vom: 9.5.2019
13. Why companies are in need of data lineage solutions

    Vom: 25.4.2019
14. What data scientists and data engineers can do with current generation serverless technologies

    Vom: 11.4.2019
15. It’s time for data scientists to collaborate with researchers in other disciplines

    Vom: 28.3.2019
16. Algorithms are shaping our lives—here’s how we wrest back control

    Vom: 14.3.2019
17. Why your attention is like a piece of contested territory

    Vom: 28.2.2019
18. The technical, societal, and cultural challenges that come with the rise of fake media

    Vom: 14.2.2019
19. Using machine learning and analytics to attract and retain employees

    Vom: 31.1.2019
20. How machine learning impacts information security

    Vom: 17.1.2019