This browser doesn't support Spotify Web Player. Switch browsers or download Spotify for your desktop.

The Data Exchange with Ben Lorica

By Ben Lorica

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/].

  1. 1.
    Taking business intelligence and analyst tools to the next level01/14/2021
    48:16
  2. 2.
    Data exchanges and their applications in healthcare and the life sciences01/07/2021
    51:51
  3. 3.
    Key AI and Data Trends for 202112/31/2020
    52:32
  4. 4.
    A Unified Management Model for Successful Data-Focused Teams12/24/2020
    47:58
  5. 5.
    Security and privacy for the disoriented12/17/2020
    46:34
  6. 6.
    The State of Responsible AI12/10/2020
    38:55
  7. 7.
    Improving the robustness of natural language applications12/03/2020
    37:35
  8. 8.
    End-to-end deep learning models for speech applications11/26/2020
    43:48
  1. 9.
    Securing machine learning applications11/19/2020
    45:40
  2. 10.
    Testing Natural Language Models11/12/2020
    30:09
  3. 11.
    Detecting Fake News11/05/2020
    32:46
  4. 12.
    The Computational Limits of Deep Learning10/29/2020
    43:04
  5. 13.
    Making deep learning accessible10/22/2020
    46:56
  6. 14.
    Building and deploying knowledge graphs10/15/2020
    49:30
  7. 15.
    Financial Time Series Forecasting with Deep Learning10/08/2020
    37:10
  8. 16.
    A programming language for scientific machine learning and differentiable programming10/01/2020
    50:17
  9. 17.
    Using machine learning to modernize medical triage and monitoring systems09/24/2020
    32:55
  10. 18.
    Connecting Reinforcement Learning to Simulation Software09/17/2020
    52:47
  11. 19.
    Using machine learning to detect shifts in government policy09/10/2020
    43:08
  12. 20.
    What is AI Assurance?09/03/2020
    38:05
  13. 21.
    Best practices for building conversational AI applications08/27/2020
    43:55
  14. 22.
    Tools for scaling machine learning08/20/2020
    39:06
  15. 23.
    From Python beginner to seasoned software engineer08/13/2020
    49:20
  16. 24.
    Assessing Models and Simulations of Epidemic Infectious Diseases08/06/2020
    43:38
  17. 25.
    Improving the hiring pipeline for software engineers07/30/2020
    52:30
  18. 26.
    How to build state-of-the-art chatbots07/23/2020
    45:12
  19. 27.
    Democratizing machine learning07/16/2020
    44:26
  20. 28.
    How graph technologies are being used to solve complex business problems07/09/2020
    49:38
  21. 29.
    Machines for unlocking the deluge of COVID-19 papers, articles, and conversations07/02/2020
    42:57
  22. 30.
    Designing machine learning models for both consumer and industrial applications06/25/2020
    33:34
  23. 31.
    Building open source developer tools for language applications06/18/2020
    43:55
  24. 32.
    Viewing machine learning and data science applications as sociotechnical systems06/11/2020
    40:34
  25. 33.
    Identifying and mitigating liabilities and risks associated with AI06/04/2020
    35:07
  26. 34.
    How machine learning is being used in quantitative finance05/28/2020
    40:04
  27. 35.
    Understanding machine learning model governance05/21/2020
    35:08
  28. 36.
    Improving performance and scalability of data science libraries05/14/2020
    33:43
  29. 37.
    Why TinyML will be huge05/07/2020
    36:49
  30. 38.
    An open source platform for training deep learning models04/30/2020
    40:44
  31. 39.
    Algorithms that continually invent both problems and solutions04/23/2020
    43:45
  32. 40.
    Computational Models and Simulations of Epidemic Infectious Diseases04/16/2020
    34:37
  33. 41.
    Human-in-the-loop machine learning04/09/2020
    43:35
  34. 42.
    Next-generation simulation software will incorporate deep reinforcement learning04/02/2020
    39:55
  35. 43.
    Business at the speed of AI: Lessons from Shopify03/26/2020
    37:12
  36. 44.
    How deep learning is being used in search and information retrieval03/19/2020
    39:50
  37. 45.
    The responsible development, deployment and operation of machine learning systems03/12/2020
    38:52
  38. 46.
    Hyperscaling natural language processing03/05/2020
    35:14
  39. 47.
    What businesses need to know about model explainability02/27/2020
    36:10
  40. 48.
    Scalable Machine Learning, Scalable Python, For Everyone02/20/2020
    35:45
  41. 49.
    Computational humanness, analogy and innovation, and soft concepts02/13/2020
    33:38
  42. 50.
    Building domain specific natural language applications02/06/2020
    33:09
  43. 51.
    The state of privacy-preserving machine learning01/30/2020
    42:15
  44. 52.
    Taking messaging and data ingestion systems to the next level01/23/2020
    38:00
  45. 53.
    Business at the speed of AI: Lessons from Rakuten01/16/2020
    41:16
  46. 54.
    The combination of the right software and commodity hardware will prove capable of handling most machine learning tasks01/09/2020
    30:23
  47. 55.
    Key AI and Data Trends for 202012/26/2019
    36:26
  48. 56.
    The evolution of TensorFlow and of machine learning infrastructure12/12/2019
    36:24
  49. 57.
    Building large-scale, real-time computer vision applications11/26/2019
    40:19
  50. 58.
    Taking stock of foundational tools for analytics and machine learning11/12/2019
    44:36

Listen to The Data Exchange with Ben Lorica now.

Listen to The Data Exchange with Ben Lorica in full in the Spotify app