國立虎尾科技大學 |

Text Analytics with Python = A Practical Real-World Approach to Gaining Actionable Insights from your Data /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Text Analytics with Python/ by Dipanjan Sarkar.
Reminder of title:	A Practical Real-World Approach to Gaining Actionable Insights from your Data /
Author:	Sarkar, Dipanjan.
Description:	XXI, 385 p. 54 illus., 33 illus. in color.online resource. :
Contained By:	Springer Nature eBook
Subject:	Big data. -
Online resource:	https://doi.org/10.1007/978-1-4842-2388-8
ISBN:	9781484223888

Text Analytics with Python = 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. - 1st ed. 2016. - XXI, 385 p. 54 illus., 33 illus. in color.online resource.

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:

981821
Big data.

LC Class. No.: QA76.9.B45

Dewey Class. No.: 005.7

Text Analytics with Python = A Practical Real-World Approach to Gaining Actionable Insights from your Data /
LDR:03259nam a22003855i 4500 001 976536
003 DE-He213
005 20200703160345.0
007 cr nn 008mamaa
008 201211s2016 xxu| s |||| 0|eng d
020 $a 9781484223888 $9 978-1-4842-2388-8
024 7 $a 10.1007/978-1-4842-2388-8 $2 doi
035 $a 978-1-4842-2388-8
050 4 $a QA76.9.B45
072 7 $a UN $2 bicssc
072 7 $a COM021000 $2 bisacsh
072 7 $a UN $2 thema
082 0 4 $a 005.7 $2 23
100 1 $a Sarkar, Dipanjan. $4 aut $4 http://id.loc.gov/vocabulary/relators/aut $3 1115985
245 1 0 $a Text Analytics with Python $h [electronic resource] : $b A Practical Real-World Approach to Gaining Actionable Insights from your Data / $c by Dipanjan Sarkar.
250 $a 1st ed. 2016.
264 1 $a Berkeley, CA : $b Apress : $b Imprint: Apress, $c 2016.
300 $a XXI, 385 p. 54 illus., 33 illus. in color. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
505 0 $a 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.-.
520 $a 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.
650 0 $a Big data. $3 981821
650 0 $a Database management. $3 557799
650 0 $a Data mining. $3 528622
650 0 $a Programming languages (Electronic computers). $3 1127615
650 1 4 $a Big Data. $3 1017136
650 2 4 $a Database Management. $3 669820
650 2 4 $a Data Mining and Knowledge Discovery. $3 677765
650 2 4 $a Programming Languages, Compilers, Interpreters. $3 669782
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9781484223871
776 0 8 $i Printed edition: $z 9781484223895
856 4 0 $u https://doi.org/10.1007/978-1-4842-2388-8
912 $a ZDB-2-CWD
912 $a ZDB-2-SXPC
950 $a Professional and Applied Computing (SpringerNature-12059)
950 $a Professional and Applied Computing (R0) (SpringerNature-43716)