877 Epizód

  1. 796: Earth's Coming Population Collapse and How AI Can Help, with Simon Kuestenmacher

    Közzétéve: 2024. 06. 28.

  2. 795: Fast-Evolving Data and AI Regulatory Frameworks, with Dr. Gina Guillaume-Joseph

    Közzétéve: 2024. 06. 25.

  3. 794: Exciting (and Frightening!) Trends in Open-Source AI

    Közzétéve: 2024. 06. 21.

  4. 793: Bayesian Methods and Applications, with Alexandre Andorra

    Közzétéve: 2024. 06. 18.

  5. 792: In Case You Missed It in May 2024

    Közzétéve: 2024. 06. 14.

  6. 791: Reinforcement Learning from Human Feedback (RLHF), with Dr. Nathan Lambert

    Közzétéve: 2024. 06. 11.

  7. 790: Open-Source Libraries for Data Science at the New York R Conference

    Közzétéve: 2024. 06. 07.

  8. 789: ML for Wind-Powered Energy Generation, with Dr. Jason Yosinski

    Közzétéve: 2024. 06. 04.

  9. 788: Multi-Agent Systems: How Teams of LLMs Excel at Complex Tasks

    Közzétéve: 2024. 05. 31.

  10. 787: MLOps: The Job and The Key Tools, with Demetrios Brinkmann

    Közzétéve: 2024. 05. 28.

  11. 786: The Six Keys to Data Scientists' Success, with Kirill Eremenko

    Közzétéve: 2024. 05. 24.

  12. 785: Math, Quantum ML and Language Embeddings, with Dr. Luis Serrano

    Közzétéve: 2024. 05. 21.

  13. 784: Aligning Large Language Models, with Sinan Ozdemir

    Közzétéve: 2024. 05. 17.

  14. 783: Generative A.I. for Solar Power Installation, with Navdeep Martin

    Közzétéve: 2024. 05. 14.

  15. 782: In Case You Missed It in April 2024

    Közzétéve: 2024. 05. 10.

  16. 781: Ensuring Successful Enterprise AI Deployments, with Sol Rashidi

    Közzétéve: 2024. 05. 07.

  17. 780: How to Become a Data Scientist, with Dr. Adam Ross Nelson

    Közzétéve: 2024. 05. 03.

  18. 779: The Tidyverse of Essential R Libraries and their Python Analogues, with Dr. Hadley Wickham

    Közzétéve: 2024. 04. 30.

  19. 778: Mixtral 8x22B: SOTA Open-Source LLM Capabilities at a Fraction of the Compute

    Közzétéve: 2024. 04. 26.

  20. 777: Generative AI in Practice, with Bernard Marr

    Közzétéve: 2024. 04. 23.

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The latest machine learning, A.I., and data career topics from across both academia and industry are brought to you by host Dr. Jon Krohn on the Super Data Science Podcast. As the quantity of data on our planet doubles every couple of years and with this trend set to continue for decades to come, there's an unprecedented opportunity for you to make a meaningful impact in your lifetime. In conversation with the biggest names in the data science industry, Jon cuts through hype to fuel that professional impact. Whether you're curious about getting started in a data career or you're a deep technical expert, whether you'd like to understand what A.I. is or you'd like to integrate more data-driven processes into your business, we have inspiring guests and lighthearted conversation for you to enjoy. We cover tools, techniques, and implementation tricks across data collection, databases, analytics, predictive modeling, visualization, software engineering, real-world applications, commercialization, and entrepreneurship − everything you need to crush it with data science.

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