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Java Data Science Cookbook

You're reading from   Java Data Science Cookbook Explore the power of MLlib, DL4j, Weka, and more

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Product type Paperback
Published in Mar 2017
Publisher Packt
ISBN-13 9781787122536
Length 372 pages
Edition 1st Edition
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Author (1):
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Rushdi Shams Rushdi Shams
Author Profile Icon Rushdi Shams
Rushdi Shams
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Toc

Table of Contents (10) Chapters Close

Preface 1. Obtaining and Cleaning Data FREE CHAPTER 2. Indexing and Searching Data 3. Analyzing Data Statistically 4. Learning from Data - Part 1 5. Learning from Data - Part 2 6. Retrieving Information from Text Data 7. Handling Big Data 8. Learn Deeply from Data 9. Visualizing Data

Introduction

Due to the availability of web data, as most of them are in text format, the type of data that a data scientist handles nowadays the most is text. There are many dimensions of text data that can be retrieved from documents, articles, blog posts, social media updates, newswires, and you name it.

Many Java-based tools are available for data scientists to retrieve information from text data. Also, there are tools that achieve a variety of data science tasks. In this chapter, we have limited our scope to a few data science tasks like trivial text feature extractions like sentences and words, document classification using machine learning, topic extraction and modelling, keyword extraction from documents, and named entity recognition.

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