Moving a machine learning model from a development environment to a functioning production system presents a distinct set of operational challenges. This chapter introduces Machine Learning Operations (MLOps), the discipline focused on building and maintaining ML systems efficiently and reliably.
We will establish a starting point for understanding MLOps by covering several key topics:
By the end of this chapter, you will have a clear understanding of what MLOps is, why it is needed, and the fundamental ideas it is built upon.
1.1 What is MLOps?
1.2 Why MLOps is Necessary for Machine Learning
1.3 MLOps vs. DevOps: Similarities and Differences
1.4 The Goals of an MLOps Strategy
1.5 Core Principles of MLOps
1.6 Common Challenges in Production Machine Learning