Automated Machine Learning on AWS

Table of Contents

Preface

Section 1: Fundamentals of the Automated Machine Learning Process and AutoML on AWS

Chapter 1: Getting Started with Automated Machine Learning on AWS

Technical requirements

Overview of the ML process

Complexities in the ML process

An example of the end-to-end ML process

Introducing ACME Fishing Logistics

The case for ML

Getting insights from the data

Building the right model

Training the model

Evaluating the trained model

Exploring possible next steps

Tuning our model

Deploying the optimized model into production

Streamlining the ML process with AutoML

How AWS makes automating the ML development and deployment process easier

Summary

Chapter 2: Automating Machine Learning Model Development Using SageMaker Autopilot