语系:
簡体中文
English
日文
繁體中文
说明
登入
回上页
到查询结果
[ author_sort:"sarkar, dipanjan." ]
切换:
标签
|
MARC模式
|
ISBD
Text analytics with Python[electroni...
~
Sarkar, Dipanjan.
Text analytics with Python[electronic resource] :a practical real-world approach to gaining actionable insights from your data /
纪录类型:
书目-语言数据,印刷品 : Monograph/item
[NT 15000414] null:
006.35
[NT 47271] Title/Author:
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.
面页册数:
xxi, 385 p. : : ill., digital ;; 24 cm.
Contained By:
Springer eBooks
标题:
Natural language processing (Computer science)
标题:
Python (Computer program language)
标题:
Computer science.
标题:
Programming languages (Electronic computers)
标题:
Database management.
标题:
Data mining.
标题:
Computer Science.
标题:
Big Data.
标题:
Database Management.
标题:
Data Mining and Knowledge Discovery.
标题:
Programming Languages, Compilers, Interpreters.
ISBN:
9781484223888
ISBN:
9781484223871
[NT 15000228] null:
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.
[NT 15000229] null:
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.
电子资源:
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 Python
a 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 /
LDR
:02842nam a2200289 a 4500
001
476806
003
DE-He213
005
20161130112528.0
006
m d
007
cr nn 008maaau
008
181208s2016 cau s 0 eng d
020
$a
9781484223888
$q
(electronic bk.)
020
$a
9781484223871
$q
(paper)
024
7
$a
10.1007/978-1-4842-2388-8
$2
doi
035
$a
978-1-4842-2388-8
040
$a
GP
$c
GP
041
0
$a
eng
050
4
$a
QA76.9.N38
082
0 4
$a
006.35
$2
23
090
$a
QA76.9.N38
$b
S245 2016
100
1
$a
Sarkar, Dipanjan.
$3
680993
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.
260
$a
Berkeley, CA :
$b
Apress :
$b
Imprint: Apress,
$c
2016.
300
$a
xxi, 385 p. :
$b
ill., digital ;
$c
24 cm.
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
Natural language processing (Computer science)
$3
411876
650
0
$a
Python (Computer program language)
$3
339754
650
0
$a
Computer science.
$3
182962
650
0
$a
Programming languages (Electronic computers)
$3
340128
650
0
$a
Database management.
$3
174575
650
0
$a
Data mining.
$3
337740
650
1 4
$a
Computer Science.
$3
423143
650
2 4
$a
Big Data.
$3
671567
650
2 4
$a
Database Management.
$3
463966
650
2 4
$a
Data Mining and Knowledge Discovery.
$3
464541
650
2 4
$a
Programming Languages, Compilers, Interpreters.
$3
466913
710
2
$a
SpringerLink (Online service)
$3
463450
773
0
$t
Springer eBooks
856
4 0
$u
http://dx.doi.org/10.1007/978-1-4842-2388-8
950
$a
Professional and Applied Computing (Springer-12059)
读者评论 0 笔
多媒体
多媒体档案
http://dx.doi.org/10.1007/978-1-4842-2388-8
评论
新增评论
分享你的心得
Export
[NT 5501410] pickup library
处理中
...
变更密码
登入