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

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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

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18. Other Books You May Enjoy

Technical requirements

You will require the following to complete this chapter:

The latest version of your preferred web browser.
The H2O software installed on your system. Refer to Chapter 1, Understanding H2O AutoML Basics, for instructions on how to install H2O on your system.

Tip

All the H2O AutoML function parameters shown in this chapter are shown using H2O Flow to keep things simple. The equivalent parameters are also available in the Python and R programming languages for software engineers to code into their services. You can find these details at https://docs.h2o.ai/h2o/latest-stable/h2o-docs/parameters.html.

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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

Technical requirements

Authors (1)

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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

Technical requirements

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Authors (1)

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