You're reading from Automated Machine Learning Hyperparameter optimization, neural architecture search, and algorithm selection with cloud platforms

Product type Paperback

Published in Feb 2021

Publisher Packt

ISBN-13 9781800567689

Length 312 pages

Edition 1st Edition

Languages

Python

Tools

Azure Functions

Concepts

Machine Learning

Author (1):

Adnan Masood

View More author details

Table of Contents (15) Chapters

Preface

1. Section 1: Introduction to Automated Machine Learning

2. Chapter 1: A Lap around Automated Machine Learning FREE CHAPTER

3. Chapter 2: Automated Machine Learning, Algorithms, and Techniques

4. Chapter 3: Automated Machine Learning with Open Source Tools and Libraries

5. Section 2: AutoML with Cloud Platforms

6. Chapter 4: Getting Started with Azure Machine Learning

7. Chapter 5: Automated Machine Learning with Microsoft Azure

8. Chapter 6: Machine Learning with AWS

9. Chapter 7: Doing Automated Machine Learning with Amazon SageMaker Autopilot

10. Chapter 8: Machine Learning with Google Cloud Platform

11. Chapter 9: Automated Machine Learning with GCP

12. Section 3: Applied Automated Machine Learning

13. Chapter 10: AutoML in the Enterprise

14. Other Books You May Enjoy

AWS JumpStart

In Dec 2020, Amazon announced SageMaker JumpStart as a capability to access pre-built model repositories also called model zoos to accelerate model development. Integrated as apart of Amazon SageMaker, JumpStart provides pre-built templates for predictive maintenance, computer vision, autonomous driving, fraud detection, credit risk prediction, OCR for extracting and analyze data from documents, churn prediction, and personalized recommendations.

JumpStart provides an excellent starting point for developers to use these pre-existing templates to JumpStart (pun intended) their development. These accelerator and starter kits are available on GitHub here. https://github.com/awslabs/ and provide recipes and best practices to use Amazon SageMaker model development and deployment mechanisms.

Further details on using AWS JumpStart can be found here. https://docs.aws.amazon.com/sagemaker/latest/dg/studio-jumpstart.html