Machine Learning model deployment can be a complicated undertaking, but it doesn’t have to be overly complex. During this 60-minute event, presented by Dr. Andrew Clark and Sid Mangalik, we will cover:

An introduction to what elements are required for ML decision assurance and reproducibility

How Monitaur supports best practices while remaining flexible to individual deployment paradigms

Full-length example of best practices when deploying a Scikit Learn pattern ML model with a REST API within a Docker container

Examples of ungovernable deployments and what not to do

Machine Learning Deployment Best Practices