60 Episodes

  1. Machine learning for operational analytics and business intelligence

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

    Published: 17/01/2019

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The O'Reilly Data Show Podcast explores the opportunities and techniques driving big data, data science, and AI.

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