281 Folgen

  1. Creating Master Data at Scale with AI

    Vom: 4.2.2021
  2. Bringing AI and computing closer to data sources

    Vom: 28.1.2021
  3. Deep Learning in the Sciences

    Vom: 21.1.2021
  4. Taking business intelligence and analyst tools to the next level

    Vom: 14.1.2021
  5. Data exchanges and their applications in healthcare and the life sciences

    Vom: 7.1.2021
  6. Key AI and Data Trends for 2021

    Vom: 31.12.2020
  7. A Unified Management Model for Successful Data-Focused Teams

    Vom: 24.12.2020
  8. Security and privacy for the disoriented

    Vom: 17.12.2020
  9. The State of Responsible AI

    Vom: 10.12.2020
  10. Improving the robustness of natural language applications

    Vom: 3.12.2020
  11. End-to-end deep learning models for speech applications

    Vom: 26.11.2020
  12. Securing machine learning applications

    Vom: 19.11.2020
  13. Testing Natural Language Models

    Vom: 12.11.2020
  14. Detecting Fake News

    Vom: 5.11.2020
  15. The Computational Limits of Deep Learning

    Vom: 29.10.2020
  16. Making deep learning accessible

    Vom: 22.10.2020
  17. Building and deploying knowledge graphs

    Vom: 15.10.2020
  18. Financial Time Series Forecasting with Deep Learning

    Vom: 8.10.2020
  19. A programming language for scientific machine learning and differentiable programming

    Vom: 1.10.2020
  20. Using machine learning to modernize medical triage and monitoring systems

    Vom: 24.9.2020

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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