Pythonテクスト解析<br>Text Analytics with Python〈1st ed.〉 : A Practical Real-World Approach to Gaining Actionable Insights from your Data

個数:1
紙書籍版価格
¥10,189
  • 電子書籍
  • ポイントキャンペーン

Pythonテクスト解析
Text Analytics with Python〈1st ed.〉 : A Practical Real-World Approach to Gaining Actionable Insights from your Data

  • 著者名:Sarkar, Dipanjan
  • 価格 ¥8,889 (本体¥8,081)
  • Apress(2016/11/30発売)
  • 春分の日の三連休!Kinoppy 電子書籍・電子洋書 全点ポイント30倍キャンペーン(~3/22)
  • ポイント 2,400pt (実際に付与されるポイントはご注文内容確認画面でご確認下さい)
  • 言語:ENG
  • ISBN:9781484223871
  • eISBN:9781484223888

ファイル: /

Description


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
  • Builda 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

Table of Contents

Chapter 1:Natural Language Basics.- Chapter 2:Python Refresher for Text Analytics.- Chapter 3:Text Processing.- Chapter 4:Text Classification.- Chapter 5:Text summarization and topic modeling.- Chapter 6:Text Clustering and Similarity analysis.- Chapter 7:Sentiment Analysis.-

最近チェックした商品