O'Reilly Data Show Podcast

60 Épisodes

1. Machine learning for operational analytics and business intelligence

   Publié: 10/10/2019
2. Machine learning and analytics for time series data

   Publié: 26/09/2019
3. Understanding deep neural networks

   Publié: 12/09/2019
4. Becoming a machine learning practitioner

   Publié: 29/08/2019
5. Labeling, transforming, and structuring training data sets for machine learning

   Publié: 15/08/2019
6. Make data science more useful

   Publié: 01/08/2019
7. Acquiring and sharing high-quality data

   Publié: 18/07/2019
8. Tools for machine learning development

   Publié: 03/07/2019
9. Enabling end-to-end machine learning pipelines in real-world applications

   Publié: 20/06/2019
10. Bringing scalable real-time analytics to the enterprise

    Publié: 09/06/2019
11. Applications of data science and machine learning in financial services

    Publié: 23/05/2019
12. Real-time entity resolution made accessible

    Publié: 09/05/2019
13. Why companies are in need of data lineage solutions

    Publié: 25/04/2019
14. What data scientists and data engineers can do with current generation serverless technologies

    Publié: 11/04/2019
15. It’s time for data scientists to collaborate with researchers in other disciplines

    Publié: 28/03/2019
16. Algorithms are shaping our lives—here’s how we wrest back control

    Publié: 14/03/2019
17. Why your attention is like a piece of contested territory

    Publié: 28/02/2019
18. The technical, societal, and cultural challenges that come with the rise of fake media

    Publié: 14/02/2019
19. Using machine learning and analytics to attract and retain employees

    Publié: 31/01/2019
20. How machine learning impacts information security

    Publié: 17/01/2019