Operational Challenges

Michael and Erik discuss the operational challenges of putting ML systems into production, highlighting the difficulties of generating and updating features in real time. They emphasize the common but often overlooked domain of bespoke engineering in managing the operational concerns of ML models.

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MLOps.community
The Future of ML and Data Platforms // Michael Del Balso - Erik Bernhardsson // Coffee Sessions #57
Related Questions
- What are the challenges in machine learning?
- What are the challenges in machine learning as discussed in the episode Challenges Operationalizing ML (And Some Solutions) // Nathan Ryan Frank // #199 and the clip Building ML Systems?