Table of contents : Brief Table of Contents (Not Yet Final) Preface Overview of this book’s mission Target Reader of this Book Introduction From ML Models to MLOps to ML Systems Supervised learning primer and what is a feature anyway? 1. Building Machine Learning Systems The Evolution of Machine Learning Systems The Anatomy of a Machine Learning System Types of Machine Learning Data Sources Tabular data Unstructured Data Event Data API-Provided Data Ethics and Laws for Data Sources Incremental Datasets What is a ML Pipeline ? Principles of MLOps Machine Learning Systems with a Feature Store Three Types of ML System with a Feature Store ML Frameworks and ML Infrastructure used in this book Summary