760 Episodes

  1. When should organizations consider data mesh?

    Published: 24/05/2021
  2. How we can fix the data science talent shortage

    Published: 16/05/2021
  3. How AIOps improves application monitoring

    Published: 15/05/2021
  4. How transfer learning jump-starts new AI projects

    Published: 14/05/2021
  5. Rethinking platform modernization using data mesh

    Published: 13/05/2021
  6. What is Apache Spark? The big data platform that crushed Hadoop

    Published: 11/05/2021
  7. What is deep reinforcement learning: The next step in AI and deep learning

    Published: 10/05/2021
  8. 3 big data platforms look beyond Hadoop

    Published: 06/05/2021
  9. Graph analysis: Not the dots, but the connections

    Published: 04/05/2021
  10. Google GPipe and Microsoft PipeDream: Scaling AI training

    Published: 02/05/2021
  11. Checking AI bias is a job for the humans

    Published: 01/05/2021
  12. How AI helped Domino’s improve pizza delivery

    Published: 30/04/2021
  13. What is NoSQL? Databases for a cloud-scale future

    Published: 28/04/2021
  14. What is data mining? How analytics uncovers insights

    Published: 28/04/2021
  15. Is your data lake open enough? What to watch out for

    Published: 28/04/2021
  16. What is big data analytics? Fast answers from diverse data sets

    Published: 28/04/2021
  17. What is a data lake? Flexible big data management explained

    Published: 28/04/2021
  18. Open source model server for PyTorch on AWS - TorchServe

    Published: 23/04/2021
  19. Exploring best machine learning and deep learning libraries

    Published: 22/04/2021
  20. What we just learned about data science — and what’s next

    Published: 22/04/2021

36 / 38

Interviews and conversations with thought leaders in Artificial Intelligence, Machine Learning and Data Science

Visit the podcast's native language site