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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):

Kamath

Krishna Choppella

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Table of Contents (13) Chapters

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

A. Linear Algebra

B. Probability

Index

Tools and usage

We will now discuss some of the most well-known tools and libraries in Java that are used in various NLP and text mining applications.

Mallet

Mallet is a Machine Learning toolkit for text written in Java, which comes with several natural language processing libraries, including those some for document classification, sequence tagging, and topic modeling, as well as various Machine Learning algorithms. It is open source, released under CPL. Mallet exposes an extensive API (see the following screenshots) to create and configure sequences of "pipes" for pre-processing, vectorizing, feature selection, and so on, as well as to extend implementations of classification and clustering algorithms, plus a host of other text analytics and Machine Learning capabilities.

KNIME

KNIME is an open platform for analytics with Open GL licensing with a number of powerful tools for conducting all aspects of data science. The Text Processing module is available for separate download from KNIME Labs...