MLOps.community

A podcast by Demetrios

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401 Episodes

  1. How to Systematically Test and Evaluate Your LLMs Apps // Gideon Mendels // #269

    Published: 10/18/2024
  2. Exploring the Impact of Agentic Workflows // Raj Rikhy // #268

    Published: 10/15/2024
  3. The Only Constant is (Data) Change // Panel // DE4AI

    Published: 10/11/2024
  4. The AI Dream Team: Strategies for ML Recruitment and Growth // Jelmer Borst and Daniela Solis // #267

    Published: 10/9/2024
  5. Making Your Company LLM-native // Francisco Ingham // #266

    Published: 10/6/2024
  6. Unpacking 3 Types of Feature Stores // Simba Khadder // #265

    Published: 10/1/2024
  7. Reinvent Yourself and Be Curious // Stefano Bosisio // MLOps Podcast #264

    Published: 9/27/2024
  8. Global Feature Store // Gottam Sai Bharath & Cole Bailey // #263

    Published: 9/24/2024
  9. RAG Quality Starts with Data Quality // Adam Kamor // #262

    Published: 9/20/2024
  10. Who's MLOps for Anyway? // Jonathan Rioux // #261

    Published: 9/17/2024
  11. Alignment is Real // Shiva Bhattacharjee // #260

    Published: 9/13/2024
  12. Ax a New Way to Build Complex Workflows with LLMs // Vikram Rangnekar // #259

    Published: 9/11/2024
  13. Building in Production Human-centred GenAI Solutions // Mohamed Abusaid & Mara Pometti// #177

    Published: 9/5/2024
  14. Visualize - Bringing Structure to Unstructured Data // Markus Stoll // #258

    Published: 9/3/2024
  15. AI Testing Highlights // Special MLOps Podcast Episode

    Published: 9/1/2024
  16. MLSecOps is Fundamental to Robust AISPM // Sean Morgan // #257

    Published: 8/30/2024
  17. MLOps for GenAI Applications // Harcharan Kabbay // #256

    Published: 8/27/2024
  18. BigQuery Feature Store // Nicolas Mauti // #255

    Published: 8/23/2024
  19. Design and Development Principles for LLMOps // Andy McMahon // #254

    Published: 8/20/2024
  20. Data Quality = Quality AI // AIQCON Panel

    Published: 8/16/2024

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Weekly talks and fireside chats about everything that has to do with the new space emerging around DevOps for Machine Learning aka MLOps aka Machine Learning Operations.