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Learn Amazon SageMaker

You're reading from Learn Amazon SageMaker A guide to building, training, and deploying machine learning models for developers and data scientists

Product type Paperback

Published in Aug 2020

Publisher Packt

ISBN-13 9781800208919

Length 490 pages

Edition 1st Edition

Languages

Python

Tools

AWS

Concepts

Machine Learning

Author (1):

Julien Simon

View More author details

Table of Contents (19) Chapters

Preface

1. Section 1: Introduction to Amazon SageMaker

2. Chapter 1: Introduction to Amazon SageMaker FREE CHAPTER

3. Chapter 2: Handling Data Preparation Techniques

4. Section 2: Building and Training Models

5. Chapter 3: AutoML with Amazon SageMaker Autopilot

6. Chapter 4: Training Machine Learning Models

7. Chapter 5: Training Computer Vision Models

8. Chapter 6: Training Natural Language Processing Models

9. Chapter 7: Extending Machine Learning Services Using Built-In Frameworks

10. Chapter 8: Using Your Algorithms and Code

11. Section 3: Diving Deeper on Training

12. Chapter 9: Scaling Your Training Jobs

13. Chapter 10: Advanced Training Techniques

14. Section 4: Managing Models in Production

15. Chapter 11: Deploying Machine Learning Models

16. Chapter 12: Automating Machine Learning Workflows

17. Chapter 13: Optimizing Prediction Cost and Performance

18. Other Books You May Enjoy

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Section 4: Managing Models in Production

In this section, you will learn how to deploy machine learning models in a variety of configurations, both with the SDK and with several automation tools. Finally, you will learn how to find the best cost/performance ratio for your prediction infrastructures.

This section comprises the following chapters:

Chapter 11, Deploying Machine Learning Models
Chapter 12, Automating Deployment Tasks
Chapter 13, Optimizing Cost and Performance

The rest of the chapter is locked

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Authors (1)

Julien Simon

Julien Simon

Julien Simon is a Principal Developer Advocate for AI & Machine Learning at Amazon Web Services. He focuses on helping developers and enterprises bring their ideas to life. He frequently speaks at conferences, blogs on the AWS Blog and on Medium, and he also runs an AI/ML podcast. Prior to joining AWS, Julien served for 10 years as CTO/VP Engineering in top-tier web startups where he led large Software and Ops teams in charge of thousands of servers worldwide. In the process, he fought his way through a wide range of technical, business and procurement issues, which helped him gain a deep understanding of physical infrastructure, its limitations and how cloud computing can help.

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