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AI Assistant (beta) to help accelerate your learning

Key benefits

Learn how to train the best models with a single click using H2O AutoML

Get a simple explanation of model performance using H2O Explainability

Easily deploy your trained models to production using H2O MOJO and POJO

Description

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.

Who is this book for?

This book is for engineers and data scientists who want to quickly adopt machine learning into their products without worrying about the internal intricacies of training ML models. If you're someone who wants to incorporate machine learning into your software system but don’t know where to start or don’t have much expertise in the domain of ML, then you’ll find this book useful. Basic knowledge of statistics and programming is beneficial. Some understanding of ML and Python will be helpful.

What you will learn

Get to grips with H2O AutoML and learn how to use it

Explore the H2O Flow Web UI

Understand how H2O AutoML trains the best models and automates hyperparameter optimization

Find out how H2O Explainability helps understand model performance

Explore H2O integration with scikit-learn, the Spring Framework, and Apache Storm

Discover how to use H2O with Spark using H2O Sparkling Water

What do you get with Print?

Instant access to your digital copy whilst your Print order is Shipped

Paperback book shipped to your preferred address

Redeem a companion digital copy on all Print orders

Access this title in our online reader with advanced features

DRM FREE - Read whenever, wherever and however you want

AI Assistant (beta) to help accelerate your learning

Frequently bought together

€31.99

Practical Automated Machine Learning Using H2O.ai

€31.99

Data Cleaning and Exploration with Machine Learning

€31.99

Total € 95.97

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Ajinkya Redkar Nov 06, 2022

Good and informative product

Amazon Verified review

Daniel Armstrong May 21, 2023

I really enjoyed this book It covers both the R and Python implementation (I lived seeing the differences).H2O and autoML in general is something I have most stayed away from, but I don't know why since the first DS tool I learned was spss modeler. After reading this book H2O is something I will definitely try in the future. I am not sure why more people don't use it, especially when starting out in DS. I can definitely see how the user interface could help people set up there project, it has database connections(SQL, hdfs, etc), nice feature visualizations, and data manipulations tools.The author did a nice job covering the wide array of models the H2O provides, as well as a detailed explanation of different performance metrics, and model explainability and feature importance, which includes some really nice visualizations.I am very intrigued by what I read in the productionization chapter. I think that productionization is far too often overlooked, and it is one of the best reasons to use H2O over other tools, especially if you use spark at your organization.I think beginners will get the most out of this book, but I think it can help a wider audience. I am not going to trade my pandas dfs for H2O dataframes but I think there is room for them to work together. I hope the author add a chapter or two to the work that H2O is doing in the NLP with LLMsOverall it was a great book and I am happy to have it on my shelfBest,Daniel Armstrong

Alexander Souza Oct 27, 2022

An incredible book for anyone starting in the AI world. The content is very clear and with several examples that make it much easier to understand.100% recommend

Gemmy Dec 25, 2022

Good content. Well thought-out examples. Provides a great way to understand and deploy your AI model without the mathematical complexities that goes along with it.

Dietmar Baur Nov 07, 2022

I already had access to the electronic version via Safari’s onlinebookshelf, but liked the content so much that I wanted to have a printed copy, for increased readability. The book finally arrived (a couple of days late) and I was disappointed by the tiny font size used. I‘m 48, wearing glasses - it’s really hard to read. If the reading experience of printed books is so bad, no wonder eBooks will replace them. Make reading tech books a real experience again, with bigger fonts and an overall better feel, please!!

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

What do you get with Print?