Automatic ML Model Containerization: Best Practices and Tools

Dive deep into the process of building machine learning models into container images for production inference in this comprehensive talk from MLOps World: Machine Learning in Production. Learn best practices for secure, multi-tenant image builds that avoid vendor lock-in from Clayton Davis, Head of Data Science, and Saumil Dave, Head of ML Engineering at Modzy. Explore tooling like chassis.ml and standards such as Open Model Interface (OMI) to streamline the containerization process. Gain valuable insights on creating a standard container specification that ensures interoperability, portability, and security for seamless integration of models into production applications. Ideal for data scientists and developers seeking to enhance their understanding of ML model containerization and deployment strategies.

What's in the Box: Automatic ML Model Containerization