Discover how Docker and containers integrate into the machine learning development lifecycle in this 40-minute workshop presented by Peter McKee, Head of Developer Relations at Docker. Learn the fundamentals of containers and progress to a comprehensive example, exploring crucial topics such as reproducibility, portability, and streamlined deployment. Gain valuable insights into implementing a Docker-based workflow for efficiently deploying machine learning models, enhancing your skills in containerization and ML model management.
Docker Based Workflow for Deploying a Machine Learning Model
Toronto Machine Learning Series (TMLS) via YouTube
Overview
Syllabus
Docker Based Workflow for Deploying a Machine Learning Model
Taught by
Toronto Machine Learning Series (TMLS)
