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Mastering Java Machine Learning

You're reading from Mastering Java Machine Learning A Java developer's guide to implementing machine learning and big data architectures

Product type Paperback

Published in Jul 2017

Publisher Packt

ISBN-13 9781785880513

Length 556 pages

Edition 1st Edition

Languages

Java

Concepts

Big Data

Authors (2):

Uday Kamath

Krishna Choppella

View More author details

Table of Contents (20) Chapters

Mastering Java Machine Learning

Credits

Foreword

About the Authors

About the Reviewers

www.PacktPub.com

Customer Feedback

Preface

1. Machine Learning Review FREE CHAPTER

2. Practical Approach to Real-World Supervised Learning

3. Unsupervised Machine Learning Techniques

4. Semi-Supervised and Active Learning

5. Real-Time Stream Machine Learning

6. Probabilistic Graph Modeling

7. Deep Learning

8. Text Mining and Natural Language Processing

9. Big Data Machine Learning – The Final Frontier

Linear Algebra

Probability

Index

Tools and usage

In this section, we will introduce two tools in Java that are very popular for probabilistic graph modeling.

OpenMarkov

OpenMarkov is a Java-based tool for PGMs and here is the description from www.openmarkov.org:

Note

OpenMarkov is a software tool for probabilistic graphical models (PGMs) developed by the Research Centre for Intelligent Decision-Support Systems of the UNED in Madrid, Spain.

It has been designed for: editing and evaluating several types of PGMs, such as Bayesian networks, influence diagrams, factored Markov models, and so on, learning Bayesian networks from data interactively, and cost-effectiveness analysis.

OpenMarkov is very good in performing interactive and automated learning from the data. It has capabilities to preprocess the data (discretization using frequency and value) and perform structure and parameter learning using a few search algorithms such as search-based Hill Climbing and score-based PC. OpenMarkov stores the models in a format known as pgmx...

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Authors (2)

Kamath

Kamath

See other products by Kamath

Krishna Choppella

Krishna Choppella

Krishna Choppella builds tools and client solutions in his role as a solutions architect for analytics at BAE Systems Applied Intelligence. He has been programming in Java for 20 years. His interests are data science, functional programming, and distributed computing.

See other products by Krishna Choppella

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