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Automated Machine Learning

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

Section 3: Applied Automated Machine Learning

This final section deals with real-world usage scenarios of automated machine learning, examining problems and case studies. In this section, the applied enterprise needs of data cleaning, feature engineering, and automation are discussed in detail with AutoML's transparency and explainability offerings.

This section comprises the following chapter:

Chapter 10, AutoML in the Enterprise

The rest of the chapter is locked

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Authors (1)

Adnan Masood

Adnan Masood

Adnan Masood, PhD is an artificial intelligence and machine learning researcher, visiting scholar at Stanford AI Lab, software engineer, Microsoft MVP (Most Valuable Professional), and Microsoft's regional director for artificial intelligence. As chief architect of AI and machine learning at UST Global, he collaborates with Stanford AI Lab and MIT CSAIL, and leads a team of data scientists and engineers building artificial intelligence solutions to produce business value and insights that affect a range of businesses, products, and initiatives.

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