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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 (13) Chapters

Preface

1. Machine Learning Review

2. Practical Approach to Real-World Supervised Learning FREE CHAPTER

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

Chapter 8. Text Mining and Natural Language Processing

Natural language processing (NLP) is ubiquitous today in various applications such as mobile apps, ecommerce websites, emails, news websites, and more. Detecting spam in e-mails, characterizing e-mails, speech synthesis, categorizing news, searching and recommending products, performing sentiment analysis on social media brands—these are all different aspects of NLP and mining text for information.

There has been an exponential increase in digital information that is textual in content—in the form of web pages, e-books, SMS messages, documents of various formats, e-mails, social media messages such as tweets and Facebook posts, now ranges in exabytes (an exabyte is 1,018 bytes). Historically, the earliest foundational work relying on automata and probabilistic modeling began in the 1950s. The 1970s saw changes such as stochastic modeling, Markov modeling, and syntactic parsing, but their progress was limited...

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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.

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