281 Epizód

  1. Connecting Reinforcement Learning to Simulation Software

    Közzétéve: 2020. 09. 17.

  2. Using machine learning to detect shifts in government policy

    Közzétéve: 2020. 09. 10.

  3. What is AI Assurance?

    Közzétéve: 2020. 09. 03.

  4. Best practices for building conversational AI applications

    Közzétéve: 2020. 08. 27.

  5. Tools for scaling machine learning

    Közzétéve: 2020. 08. 20.

  6. From Python beginner to seasoned software engineer

    Közzétéve: 2020. 08. 13.

  7. Assessing Models and Simulations of Epidemic Infectious Diseases

    Közzétéve: 2020. 08. 06.

  8. Improving the hiring pipeline for software engineers

    Közzétéve: 2020. 07. 30.

  9. How to build state-of-the-art chatbots

    Közzétéve: 2020. 07. 23.

  10. Democratizing machine learning

    Közzétéve: 2020. 07. 16.

  11. How graph technologies are being used to solve complex business problems

    Közzétéve: 2020. 07. 09.

  12. Machines for unlocking the deluge of COVID-19 papers, articles, and conversations

    Közzétéve: 2020. 07. 02.

  13. Designing machine learning models for both consumer and industrial applications

    Közzétéve: 2020. 06. 25.

  14. Building open source developer tools for language applications

    Közzétéve: 2020. 06. 18.

  15. Viewing machine learning and data science applications as sociotechnical systems

    Közzétéve: 2020. 06. 11.

  16. Identifying and mitigating liabilities and risks associated with AI

    Közzétéve: 2020. 06. 04.

  17. How machine learning is being used in quantitative finance

    Közzétéve: 2020. 05. 28.

  18. Understanding machine learning model governance

    Közzétéve: 2020. 05. 21.

  19. Improving performance and scalability of data science libraries

    Közzétéve: 2020. 05. 14.

  20. Why TinyML will be huge

    Közzétéve: 2020. 05. 07.

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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