34 Avsnitt

  1. 📡 Building Scalable ML Models with Natanel Davidovits

    Publicerades: 2024-12-16
  2. 💼 AI in the Enterprise with Jeremie Dreyfuss

    Publicerades: 2024-10-31
  3. 🌲 Machine Learning in Agriculture: Scaling AI for Crop Management with Dror Haor

    Publicerades: 2024-09-15
  4. 📊 Data-Driven Decisions: ML in E-Commerce Forecasting with Federico Bacci

    Publicerades: 2024-08-15
  5. 🚗 Driving Innovation: Machine Learning in Auto Claims Processing

    Publicerades: 2024-07-15
  6. 🚑 ML in the Emergency Room with Ljubomir Buturovic

    Publicerades: 2024-06-10
  7. 🌊 AI-Native with Idan Gazit – The future of AI products and interfaces + Getting AI to production

    Publicerades: 2024-05-16
  8. 🍪 Machine Learning in the cookie-less era with Uri Goren

    Publicerades: 2024-04-18
  9. 🛰️ Modern & Realistic MLOps with Han-chung Lee

    Publicerades: 2024-03-18
  10. 🩻 AI in Medical Devices & Medicine with Mila Orlovsky

    Publicerades: 2024-02-15
  11. ⏪ Making LLMs Backwards Compatible with Jason Liu

    Publicerades: 2024-01-15
  12. 🔴 Live MLOps Podcast – Building, Deploying and Monitoring Large Language Models with Jinen Setpal

    Publicerades: 2023-09-06
  13. Live MLOps Podcast Episode!

    Publicerades: 2023-08-28
  14. ⛹️‍♂️ Large Scale Video ML at WSC Sports with Yuval Gabay

    Publicerades: 2023-08-07
  15. 🤖 GPTs & Large Language Models in production with Hamel Husain

    Publicerades: 2023-06-20
  16. 🫣 Is Data Science a dying job? with Almog Baku

    Publicerades: 2023-05-23
  17. 🏃‍♀️Moving Fast and Breaking Data with Shreya Shankar

    Publicerades: 2023-03-30
  18. 🚴‍♀️ Quick & Dirty Machine Learning with Noa Weiss

    Publicerades: 2023-02-21
  19. ✍️ Building ML Teams and Platforms with Assaf Pinhasi

    Publicerades: 2023-01-23
  20. 🎨 Stable Diffusion and generative models with David Marx

    Publicerades: 2023-01-19

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A podcast from DagsHub about bringing machine learning into the real world. Each episode features a conversation with top data science and machine learning practitioners, who'll share their thoughts, best practices, and tips for promoting machine learning to production

Visit the podcast's native language site