You're reading from Automated Machine Learning on AWS Fast-track the development of your production-ready machine learning applications the AWS way

Product type Paperback

Published in Apr 2022

Publisher Packt

ISBN-13 9781801811828

Length 420 pages

Edition 1st Edition

Tools

AWS

Concepts

Machine Learning

Author (1):

Trenton Potgieter

View More author details

Table of Contents (18) Chapters

Preface

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

2. Chapter 1: Getting Started with Automated Machine Learning on AWS FREE CHAPTER

3. Chapter 2: Automating Machine Learning Model Development Using SageMaker Autopilot

4. Chapter 3: Automating Complicated Model Development with AutoGluon

5. Section 2: Automating the Machine Learning Process with Continuous Integration and Continuous Delivery (CI/CD)

6. Chapter 4: Continuous Integration and Continuous Delivery (CI/CD) for Machine Learning

7. Chapter 5: Continuous Deployment of a Production ML Model

8. Section 3: Optimizing a Source Code-Centric Approach to Automated Machine Learning

9. Chapter 6: Automating the Machine Learning Process Using AWS Step Functions

10. Chapter 7: Building the ML Workflow Using AWS Step Functions

11. Section 4: Optimizing a Data-Centric Approach to Automated Machine Learning

12. Chapter 8: Automating the Machine Learning Process Using Apache Airflow

13. Chapter 9: Building the ML Workflow Using Amazon Managed Workflows for Apache Airflow

14. Section 5: Automating the End-to-End Production Application on AWS

15. Chapter 10: An Introduction to the Machine Learning Software Development Life Cycle (MLSDLC)

16. Chapter 11: Continuous Integration, Deployment, and Training for the MLSDLC

17. Other Books You May Enjoy

Section 3: Optimizing a Source Code-Centric Approach to Automated Machine Learning

This section will introduce you to the limitations of the overall CI/CD process and how to further integrate the role of the ML practitioner into the pipeline build process. The section will also introduce how this role integration streamlines the automation process and present you with an optimized methodology by introducing you to AWS Step Functions.

This section comprises the following chapters:

Chapter 6, Automating the Machine Learning Process Using AWS Step Functions
Chapter 7, Building the ML Workflow Using AWS Step Functions

The rest of the chapter is locked

You're reading from Automated Machine Learning on AWS Fast-track the development of your production-ready machine learning applications the AWS way

Table of Contents (18) Chapters

Section 3: Optimizing a Source Code-Centric Approach to Automated Machine Learning

Authors (1)

Personalised recommendations for you

You're reading from Automated Machine Learning on AWS Fast-track the development of your production-ready machine learning applications the AWS way

Table of Contents (18) Chapters

Section 3: Optimizing a Source Code-Centric Approach to Automated Machine Learning

Unlock this book and the full library FREE for 7 days

Authors (1)

Personalised recommendations for you