Learn Amazon SageMaker

Learn Amazon SageMaker, 2nd Edition provides software engineers, data scientists, machine learning developers, and AWS users with direct instruction for building, training, and deploying machine learning models. Authored by Julien Simon, this reference volume addresses the operational requirements of managing end-to-end machine learning workflows within cloud infrastructure.

The text presents systematic approaches to data annotation and data preparation prior to model creation. Technical teams explore how to process raw datasets and organize feature sets using SageMaker Data Wrangler alongside SageMaker Feature Store. In addition, the material covers AutoML features designed to build and train models using Autopilot functionality.

Subsequent chapters detail precise procedures to automate deployment tasks across various host configurations using SDK utilities and native automation tools. The volume provides cloud engineers and technical developers with targeted practice for organizing, executing, and maintaining scalable model operations. It establishes an operational roadmap for technical teams configuring cloud ML pipelines.