60 Episoade

  1. What machine learning engineers need to know

    Publicat: 29.03.2018
  2. How to train and deploy deep learning at scale

    Publicat: 15.03.2018
  3. Using machine learning to monitor and optimize chatbots

    Publicat: 06.03.2018
  4. Unleashing the potential of reinforcement learning

    Publicat: 01.03.2018
  5. Graphs as the front end for machine learning

    Publicat: 15.02.2018
  6. Machine learning needs machine teaching

    Publicat: 01.02.2018
  7. How machine learning can be used to write more secure computer programs

    Publicat: 18.01.2018
  8. Bringing AI into the enterprise

    Publicat: 04.01.2018
  9. How machine learning will accelerate data management systems

    Publicat: 21.12.2017
  10. Machine learning at Spotify: You are what you stream

    Publicat: 07.12.2017
  11. The current state of Apache Kafka

    Publicat: 22.11.2017
  12. Building a natural language processing library for Apache Spark

    Publicat: 09.11.2017
  13. Machine intelligence for content distribution, logistics, smarter cities, and more

    Publicat: 26.10.2017
  14. Vehicle-to-vehicle communication networks can help fuel smart cities

    Publicat: 12.10.2017
  15. Transforming organizations through analytics centers of excellence

    Publicat: 28.09.2017
  16. The state of machine learning in Apache Spark

    Publicat: 14.09.2017
  17. Effective mechanisms for searching the space of machine learning algorithms

    Publicat: 31.08.2017
  18. How Ray makes continuous learning accessible and easy to scale

    Publicat: 17.08.2017
  19. Why AI and machine learning researchers are beginning to embrace PyTorch

    Publicat: 03.08.2017
  20. How big data and AI will reshape the automotive industry

    Publicat: 20.07.2017

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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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