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Text Analytics with Python

A Practical Real-World Approach to Gaining Actionable Insights from your Data

Text Analytics with Python by Dipanjan Sarkar
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Derive useful insights from your data using Python. You will learn both basic and advanced concepts, including text and language syntax, structure, and semantics. You will focus on algorithms and techniques, such as text classification, clustering, topic modeling, and text summarization.

Text Analytics with Python teaches you the techniques related to natural language processing and text analytics, and you will gain the skills to know which technique is best suited to solve a particular problem. You will look at each technique and algorithm with both a bird's eye view to understand how it can be used as well as with a microscopic view to understand the mathematical concepts and to implement them to solve your own problems.

What You Will Learn:

  • Understand the major concepts and techniques of natural language processing (NLP) and text analytics, including syntax and structure
  • Build a text classification system to categorize news articles, analyze app or game reviews using topic modeling and text summarization, and cluster popular movie synopses and analyze the sentiment of movie reviews
  • Implement Python and popular open source libraries in NLP and text analytics, such as the natural language toolkit (nltk), gensim, scikit-learn, spaCy and Pattern


Who This Book Is For :

IT professionals, analysts, developers, linguistic experts, data scientists, and anyone with a keen interest in linguistics, analytics, and generating insights from textual data

Apress; November 2016
397 pages; ISBN 9781484223888
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Title: Text Analytics with Python
Author: Dipanjan Sarkar
 
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