You're reading from Machine Learning at Scale with H2O A practical guide to building and deploying machine learning models on enterprise systems

Product type Paperback

Published in Jul 2022

Publisher Packt

ISBN-13 9781800566019

Length 396 pages

Edition 1st Edition

Tools

H2O

Concepts

Machine Learning

Authors (2):

Gregory Keys

David Whiting

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Table of Contents (22) Chapters

Preface

1. Section 1 – Introduction to the H2O Machine Learning Platform for Data at Scale

2. Chapter 1: Opportunities and Challenges FREE CHAPTER

3. Chapter 2: Platform Components and Key Concepts

4. Chapter 3: Fundamental Workflow – Data to Deployable Model

5. Section 2 – Building State-of-the-Art Models on Large Data Volumes Using H2O

6. Chapter 4: H2O Model Building at Scale – Capability Articulation

7. Chapter 5: Advanced Model Building – Part I

8. Chapter 6: Advanced Model Building – Part II

9. Chapter 7: Understanding ML Models

10. Chapter 8: Putting It All Together

11. Section 3 – Deploying Your Models to Production Environments

12. Chapter 9: Production Scoring and the H2O MOJO

13. Chapter 10: H2O Model Deployment Patterns

14. Section 4 – Enterprise Stakeholder Perspectives

15. Chapter 11: The Administrator and Operations Views

16. Chapter 12: The Enterprise Architect and Security Views

17. Section 5 – Broadening the View – Data to AI Applications with the H2O AI Cloud Platform

18. Chapter 13: Introducing H2O AI Cloud

19. Chapter 14: H2O at Scale in a Larger Platform Context

20. Other Books You May Enjoy

Appendix : Alternative Methods to Launch H2O Clusters

Local Sparkling Water cluster

Running Sparkling Water locally is similar to running H2O-3 locally, but with Spark dependencies. See this link for a full explanation of the Spark, Python, and H2O components involved: https://docs.h2o.ai/sparkling-water/3.2/latest-stable/doc/pysparkling.html.

We will be using Spark 3.2 here. To use a different version of Spark, go to the Sparkling Water section of the H2O downloads page at the following link: https://h2o.ai/resources/download/.

For your Sparkling Water Python client, you must use Python 2.7.x, 3.5.x, 3.6.x, or 3.7.x. We will be running Sparkling Water from a Jupyter notebook here.

Step 1 – Install Spark locally

Follow these steps to install Spark locally:

Go to https://spark.apache.org/downloads.html to download Spark. Make the following choices and then download:
- Spark version: 3.2.x
- Package type: Pre-built for Hadoop 3.3 and later
Unzip the downloaded file.
Set the following environment variables...

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You're reading from Machine Learning at Scale with H2O A practical guide to building and deploying machine learning models on enterprise systems

Table of Contents (22) Chapters

Local Sparkling Water cluster

Step 1 – Install Spark locally

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Authors (2)

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