Book Image

Machine Learning at Scale with H2O

By : Gregory Keys, David Whiting
Book Image

Machine Learning at Scale with H2O

By: Gregory Keys, David Whiting

Overview of this book

H2O is an open source, fast, and scalable machine learning framework that allows you to build models using big data and then easily productionalize them in diverse enterprise environments. Machine Learning at Scale with H2O begins with an overview of the challenges faced in building machine learning models on large enterprise systems, and then addresses how H2O helps you to overcome them. You’ll start by exploring H2O’s in-memory distributed architecture and find out how it enables you to build highly accurate and explainable models on massive datasets using your favorite ML algorithms, language, and IDE. You’ll also get to grips with the seamless integration of H2O model building and deployment with Spark using H2O Sparkling Water. You’ll then learn how to easily deploy models with H2O MOJO. Next, the book shows you how H2O Enterprise Steam handles admin configurations and user management, and then helps you to identify different stakeholder perspectives that a data scientist must understand in order to succeed in an enterprise setting. Finally, you’ll be introduced to the H2O AI Cloud platform and explore the entire machine learning life cycle using multiple advanced AI capabilities. By the end of this book, you’ll be able to build and deploy advanced, state-of-the-art machine learning models for your business needs.
Table of Contents (22 chapters)
1
Section 1 – Introduction to the H2O Machine Learning Platform for Data at Scale
5
Section 2 – Building State-of-the-Art Models on Large Data Volumes Using H2O
11
Section 3 – Deploying Your Models to Production Environments
14
Section 4 – Enterprise Stakeholder Perspectives
17
Section 5 – Broadening the View – Data to AI Applications with the H2O AI Cloud Platform

Technical requirements

For this chapter, we will focus on using Enterprise Steam to launch H2O clusters on an enterprise server cluster. Enterprise Steam technically is not required to launch H2O clusters but enterprise stakeholders typically view Enterprise Steam as a security, governance, and administrator requirement for implementing H2O in enterprise environments.

Enterprise Steam requires a license purchased from H2O.ai. If your organization does not have an instance of Enterprise Steam installed, you can access Enterprise Steam and an enterprise server cluster through a temporary trial license of the larger H2O platform. Alternatively, for ease of conducting the exercises in this book, you may wish to launch H2O clusters as a sandbox in your local environment (for example, on your laptop or desktop workstation) and bypass the use of Enterprise Steam.

See Appendix – Alternative Methods to Launch H2O Clusters for this Book to help you decide on how you wish to launch...