Book Image

Practical Automated Machine Learning Using H2O.ai

By : Salil Ajgaonkar
Book Image

Practical Automated Machine Learning Using H2O.ai

By: Salil Ajgaonkar

Overview of this book

With the huge amount of data being generated over the internet and the benefits that Machine Learning (ML) predictions bring to businesses, ML implementation has become a low-hanging fruit that everyone is striving for. The complex mathematics behind it, however, can be discouraging for a lot of users. This is where H2O comes in – it automates various repetitive steps, and this encapsulation helps developers focus on results rather than handling complexities. You’ll begin by understanding how H2O’s AutoML simplifies the implementation of ML by providing a simple, easy-to-use interface to train and use ML models. Next, you’ll see how AutoML automates the entire process of training multiple models, optimizing their hyperparameters, as well as explaining their performance. As you advance, you’ll find out how to leverage a Plain Old Java Object (POJO) and Model Object, Optimized (MOJO) to deploy your models to production. Throughout this book, you’ll take a hands-on approach to implementation using H2O that’ll enable you to set up your ML systems in no time. By the end of this H2O book, you’ll be able to train and use your ML models using H2O AutoML, right from experimentation all the way to production without a single need to understand complex statistics or data science.
Table of Contents (19 chapters)
1
Part 1 H2O AutoML Basics
4
Part 2 H2O AutoML Deep Dive
10
Part 3 H2O AutoML Advanced Implementation and Productization

Working with H2O Flow (H2O’s Web UI)

Machine Learning (ML) is more than just code. It involves tons of observations from different perspectives. As powerful as actual coding is, a lot of information gets hidden away behind the Terminal on which you code. Humans have always understood pictures more easily than words. Similarly, as complex as ML is, it can be very easy and fun to implement with the help of interactive User Interfaces (UIs). Working with a colorful UI over the dull black and white pixelated Terminal is always a plus when learning about difficult topics.

H2O Flow is a web-based UI developed by the H2O.ai team. This interface works on the same backend that we learned about in Chapter 1, Understanding H2O AutoML Basics. It is simply a web UI wrapped over the main H2O library, which passes inputs and triggers functions on the backend server and reads the results by displaying them back to the user.

In this chapter, we will learn how to work with H2O Flow. We...