You're reading from Practical Automated Machine Learning Using H2O.ai Discover the power of automated machine learning, from experimentation through to deployment to production

Product type Paperback

Published in Sep 2022

Publisher Packt

ISBN-13 9781801074520

Length 396 pages

Edition 1st Edition

Tools

H2O

Concepts

Machine Learning

Author (1):

Salil Ajgaonkar

View More author details

Table of Contents (19) Chapters

Preface

1. Part 1 H2O AutoML Basics

2. Chapter 1: Understanding H2O AutoML Basics FREE CHAPTER

3. Chapter 2: Working with H2O Flow (H2O’s Web UI)

4. Part 2 H2O AutoML Deep Dive

5. Chapter 3: Understanding Data Processing

6. Chapter 4: Understanding H2O AutoML Architecture and Training

7. Chapter 5: Understanding AutoML Algorithms

8. Chapter 6: Understanding H2O AutoML Leaderboard and Other Performance Metrics

9. Chapter 7: Working with Model Explainability

10. Part 3 H2O AutoML Advanced Implementation and Productization

11. Chapter 8: Exploring Optional Parameters for H2O AutoML

12. Chapter 9: Exploring Miscellaneous Features in H2O AutoML

13. Chapter 10: Working with Plain Old Java Objects (POJOs)

14. Chapter 11: Working with Model Object, Optimized (MOJO)

15. Chapter 12: Working with H2O AutoML and Apache Spark

16. Chapter 13: Using H2O AutoML with Other Technologies

17. Index

Why subscribe?

18. Other Books You May Enjoy

To get the most out of this book

Basic knowledge of statistics and programming is beneficial. Some understanding of ML and Python will be helpful. You will need Python installed on your computer, preferably with version 3.7 or above, or R installed on your computer with version 4.0 or above. All code examples have been tested using Python 3.10 and R 4.1.2 on Windows 10 OS and Ubuntu 22.04.1 LTS. However, they should work with future version releases too.

Software/hardware covered in the book	Operating system requirements
Python 3.10	Windows, macOS, or Linux
R 4.1.2
H2O 3.36.1.4
Java 11
Spark 3.2
Scala 2.13
Maven 3.8.6

If you are using the digital version of this book, we advise you to type the code yourself or access the code from the book’s GitHub repository (a link is available in the next section). Doing so will help you avoid any potential errors related to the copying and pasting of code.

The rest of the chapter is locked

You're reading from Practical Automated Machine Learning Using H2O.ai Discover the power of automated machine learning, from experimentation through to deployment to production

Table of Contents (19) Chapters

To get the most out of this book

Authors (1)

Personalised recommendations for you

You're reading from Practical Automated Machine Learning Using H2O.ai Discover the power of automated machine learning, from experimentation through to deployment to production

Table of Contents (19) Chapters

To get the most out of this book

Unlock this book and the full library FREE for 7 days

Authors (1)

Personalised recommendations for you