281 Epizód

  1. An open source platform for training deep learning models

    Közzétéve: 2020. 04. 30.

  2. Algorithms that continually invent both problems and solutions

    Közzétéve: 2020. 04. 23.

  3. Computational Models and Simulations of Epidemic Infectious Diseases

    Közzétéve: 2020. 04. 16.

  4. Human-in-the-loop machine learning

    Közzétéve: 2020. 04. 09.

  5. Next-generation simulation software will incorporate deep reinforcement learning

    Közzétéve: 2020. 04. 02.

  6. Business at the speed of AI: Lessons from Shopify

    Közzétéve: 2020. 03. 26.

  7. How deep learning is being used in search and information retrieval

    Közzétéve: 2020. 03. 19.

  8. The responsible development, deployment and operation of machine learning systems

    Közzétéve: 2020. 03. 12.

  9. Hyperscaling natural language processing

    Közzétéve: 2020. 03. 05.

  10. What businesses need to know about model explainability

    Közzétéve: 2020. 02. 27.

  11. Scalable Machine Learning, Scalable Python, For Everyone

    Közzétéve: 2020. 02. 20.

  12. Computational humanness, analogy and innovation, and soft concepts

    Közzétéve: 2020. 02. 13.

  13. Building domain specific natural language applications

    Közzétéve: 2020. 02. 06.

  14. The state of privacy-preserving machine learning

    Közzétéve: 2020. 01. 30.

  15. Taking messaging and data ingestion systems to the next level

    Közzétéve: 2020. 01. 23.

  16. Business at the speed of AI: Lessons from Rakuten

    Közzétéve: 2020. 01. 16.

  17. The combination of the right software and commodity hardware will prove capable of handling most machine learning tasks

    Közzétéve: 2020. 01. 09.

  18. Key AI and Data Trends for 2020

    Közzétéve: 2019. 12. 26.

  19. The evolution of TensorFlow and of machine learning infrastructure

    Közzétéve: 2019. 12. 12.

  20. Building large-scale, real-time computer vision applications

    Közzétéve: 2019. 11. 26.

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A series of informal conversations with thought leaders, researchers, practitioners, and writers on a wide range of topics in technology, science, and of course big data, data science, artificial intelligence, and related applications. Anchored by Ben Lorica (@BigData), the Data Exchange also features a roundup of the most important stories from the worlds of data, machine learning and AI. Detailed show notes for each episode can be found on https://thedataexchange.media/ The Data Exchange podcast is a production of Gradient Flow [https://gradientflow.com/].

Visit the podcast's native language site