34 Afleveringen

  1. 📡 Building Scalable ML Models with Natanel Davidovits

    Gepubliceerd: 16-12-2024

  2. 💼 AI in the Enterprise with Jeremie Dreyfuss

    Gepubliceerd: 31-10-2024

  3. 🌲 Machine Learning in Agriculture: Scaling AI for Crop Management with Dror Haor

    Gepubliceerd: 15-9-2024

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

    Gepubliceerd: 15-8-2024

  5. 🚗 Driving Innovation: Machine Learning in Auto Claims Processing

    Gepubliceerd: 15-7-2024

  6. 🚑 ML in the Emergency Room with Ljubomir Buturovic

    Gepubliceerd: 10-6-2024

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

    Gepubliceerd: 16-5-2024

  8. 🍪 Machine Learning in the cookie-less era with Uri Goren

    Gepubliceerd: 18-4-2024

  9. 🛰️ Modern & Realistic MLOps with Han-chung Lee

    Gepubliceerd: 18-3-2024

  10. 🩻 AI in Medical Devices & Medicine with Mila Orlovsky

    Gepubliceerd: 15-2-2024

  11. ⏪ Making LLMs Backwards Compatible with Jason Liu

    Gepubliceerd: 15-1-2024

  12. 🔴 Live MLOps Podcast – Building, Deploying and Monitoring Large Language Models with Jinen Setpal

    Gepubliceerd: 6-9-2023

  13. Live MLOps Podcast Episode!

    Gepubliceerd: 28-8-2023

  14. ⛹️‍♂️ Large Scale Video ML at WSC Sports with Yuval Gabay

    Gepubliceerd: 7-8-2023

  15. 🤖 GPTs & Large Language Models in production with Hamel Husain

    Gepubliceerd: 20-6-2023

  16. 🫣 Is Data Science a dying job? with Almog Baku

    Gepubliceerd: 23-5-2023

  17. 🏃‍♀️Moving Fast and Breaking Data with Shreya Shankar

    Gepubliceerd: 30-3-2023

  18. 🚴‍♀️ Quick & Dirty Machine Learning with Noa Weiss

    Gepubliceerd: 21-2-2023

  19. ✍️ Building ML Teams and Platforms with Assaf Pinhasi

    Gepubliceerd: 23-1-2023

  20. 🎨 Stable Diffusion and generative models with David Marx

    Gepubliceerd: 19-1-2023

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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