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Text analytics with Python[electronic resource] :a practical real-world approach to gaining actionable insights from your data /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
杜威分類號:	006.35
書名/作者:	Text analytics with Python : a practical real-world approach to gaining actionable insights from your data // by Dipanjan Sarkar.
作者:	Sarkar, Dipanjan.
出版者:	Berkeley, CA : : Apress :, 2016.
面頁冊數:	xxi, 385 p. : : ill., digital ;; 24 cm.
Contained By:	Springer eBooks
標題:	Natural language processing (Computer science)
標題:	Python (Computer program language)
標題:	Computer science.
標題:	Programming languages (Electronic computers)
標題:	Database management.
標題:	Data mining.
標題:	Computer Science.
標題:	Big Data.
標題:	Database Management.
標題:	Data Mining and Knowledge Discovery.
標題:	Programming Languages, Compilers, Interpreters.
ISBN:	9781484223888
ISBN:	9781484223871
內容註:	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.
摘要、提要註:	Derive useful insights from your data using Python. Learn the techniques related to natural language processing and text analytics, and gain the skills to know which technique is best suited to solve a particular problem. Text Analytics with Python teaches you both basic and advanced concepts, including text and language syntax, structure, semantics. You will focus on algorithms and techniques, such as text classification, clustering, topic modeling, and text summarization. A structured and comprehensive approach is followed in this book so that readers with little or no experience do not find themselves overwhelmed. You will start with the basics of natural language and Python and move on to advanced analytical and machine learning concepts. 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. This book: Provides complete coverage of the major concepts and techniques of natural language processing (NLP) and text analytics Includes practical real-world examples of techniques for implementation, such as building a text classification system to categorize news articles, analyzing app or game reviews using topic modeling and text summarization, and clustering popular movie synopses and analyzing the sentiment of movie reviews Shows implementations based on Python and several popular open source libraries in NLP and text analytics, such as the natural language toolkit (nltk), gensim, scikit-learn, spaCy and Pattern.
電子資源:	http://dx.doi.org/10.1007/978-1-4842-2388-8

Text analytics with Python[electronic resource] :a practical real-world approach to gaining actionable insights from your data /
Sarkar, Dipanjan.

Text analytics with Pythona practical real-world approach to gaining actionable insights from your data /[electronic resource] :by Dipanjan Sarkar. - Berkeley, CA :Apress :2016. - xxi, 385 p. :ill., digital ;24 cm.

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.

Derive useful insights from your data using Python. Learn the techniques related to natural language processing and text analytics, and gain the skills to know which technique is best suited to solve a particular problem. Text Analytics with Python teaches you both basic and advanced concepts, including text and language syntax, structure, semantics. You will focus on algorithms and techniques, such as text classification, clustering, topic modeling, and text summarization. A structured and comprehensive approach is followed in this book so that readers with little or no experience do not find themselves overwhelmed. You will start with the basics of natural language and Python and move on to advanced analytical and machine learning concepts. 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. This book: Provides complete coverage of the major concepts and techniques of natural language processing (NLP) and text analytics Includes practical real-world examples of techniques for implementation, such as building a text classification system to categorize news articles, analyzing app or game reviews using topic modeling and text summarization, and clustering popular movie synopses and analyzing the sentiment of movie reviews Shows implementations based on Python and several popular open source libraries in NLP and text analytics, such as the natural language toolkit (nltk), gensim, scikit-learn, spaCy and Pattern.

ISBN: 9781484223888

Standard No.: 10.1007/978-1-4842-2388-8doiSubjects--Topical Terms:

411876
Natural language processing (Computer science)

LC Class. No.: QA76.9.N38

Dewey Class. No.: 006.35

Text analytics with Python[electronic resource] :a practical real-world approach to gaining actionable insights from your data /
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