MARC record from Internet Archive

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100 1 $aSarkar, Dipanjan,$eauthor.
245 10 $aText analytics with Python :$ba practical real-world approach to gaining actionable insights from your data /$cDipanjan Sarkar.
264 1 $a[United States] :$bApress,$c2016.
264 2 $aNew York, NY :$bDistributed to the Book trade worldwide by Springer
264 4 $c©2016
300 $a1 online resource
336 $atext$btxt$2rdacontent
337 $acomputer$bc$2rdamedia
338 $aonline resource$bcr$2rdacarrier
347 $atext file$bPDF$2rda
505 0 $aAt a Glance; Contents; About the Author; About the Technical Reviewer; Acknowledgments; Introduction; Chapter 1: Natural Language Basics; Natural Language; What Is Natural Language?; The Philosophy of Language; Language Acquisition and Usage; Language Acquisition and Cognitive Learning; Language Usage; Linguistics; Language Syntax and Structure; Words; Phrases; Clauses; Grammar; Dependency grammars; Constituency Grammars; Word Order Typology; Language Semantics; Lexical Semantic Relations; Lemmas and Wordforms; Homonyms, Homographs, and Homophones; Heteronyms and Heterographs.
505 8 $aPolysemesCapitonyms; Synonyms and Antonyms; Hyponyms and Hypernyms; Semantic Networks and Models; Representation of Semantics; Propositional Logic; First Order Logic; Text Corpora; Corpora Annotation and Utilities; Popular Corpora; Accessing Text Corpora; Accessing the Brown Corpus; Accessing the Reuters Corpus; Accessing the WordNet Corpus; Natural Language Processing; Machine Translation; Speech Recognition Systems; Question Answering Systems; Contextual Recognition and Resolution; Text Summarization; Text Categorization; Text Analytics; Summary; Chapter 2: Python Refresher.
505 8 $aGetting to Know PythonThe Zen of Python; Applications: When Should You Use Python?; Drawbacks: When Should You Not Use Python?; Python Implementations and Versions; Installation and Setup; Which Python Version?; Which Operating System?; Integrated Development Environments; Environment Setup; Virtual Environments; Python Syntax and Structure; Data Structures and Types; Numeric Types; Strings; Lists; Sets; Dictionaries; Tuples; Files; Miscellaneous; Controlling Code Flow; Conditional Constructs; Looping Constructs; Handling Exceptions; Functional Programming; Functions; Recursive Functions.
505 8 $aAnonymous FunctionsIterators; Comprehensions; Generators; The itertools and functools Modules; Classes; Working with Text; String Literals; String Operations and Methods; Basic Operations; Indexing and Slicing; Methods; Formatting; Regular Expressions (Regexes); Text Analytics Frameworks; Summary; Chapter 3: Processing and Understanding Text; Text Tokenization; Sentence Tokenization; Word Tokenization; Text Normalization; Cleaning Text; Tokenizing Text; Removing Special Characters; Expanding Contractions; Case Conversions; Removing Stopwords; Correcting Words; Correcting Repeating Characters.
505 8 $aCorrecting SpellingsStemming; Lemmatization; Understanding Text Syntax and Structure; Installing Necessary Dependencies; Important Machine Learning Concepts; Parts of Speech (POS) Tagging; Recommended POS Taggers; Building Your Own POS Taggers; Shallow Parsing; Recommended Shallow Parsers; Building Your Own Shallow Parsers; Dependency-based Parsing; Recommended Dependency Parsers; Building Your Own Dependency Parsers; Constituency-based Parsing; Recommended Constituency Parsers; Building Your Own Constituency Parsers; Summary; Chapter 4: Text Classification; What Is Text Classification?
500 $aIncludes index.
588 0 $aOnline resource; title from PDF title page (SpringerLink, viewed January 3, 2017).
520 $aDerive 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 $aNatural language processing (Computer science)
650 0 $aPython (Computer program language)
650 0 $aComputer science.
650 0 $aProgramming languages (Electronic computers)
650 0 $aDatabase management.
650 0 $aData mining.
650 2 $aNatural Language Processing
650 2 $aElectronic Data Processing
650 2 $aData Mining
650 6 $aTraitement automatique des langues naturelles.
650 6 $aPython (Langage de programmation)
650 6 $aInformatique.
650 6 $aBases de données$xGestion.
650 6 $aExploration de données (Informatique)
650 7 $aDatabases.$2bicssc
650 7 $aData mining.$2bicssc
650 7 $aProgramming & scripting languages: general.$2bicssc
650 7 $aCOMPUTERS$xGeneral.$2bisacsh
650 7 $aComputer science.$2fast$0(OCoLC)fst00872451
650 7 $aData mining.$2fast$0(OCoLC)fst00887946
650 7 $aDatabase management.$2fast$0(OCoLC)fst00888037
650 7 $aNatural language processing (Computer science)$2fast$0(OCoLC)fst01034365
650 7 $aProgramming languages (Electronic computers)$2fast$0(OCoLC)fst01078704
650 7 $aPython (Computer program language)$2fast$0(OCoLC)fst01084736
655 0 $aElectronic books.
655 4 $aElectronic books.
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