Text analytics with Python : a practical real-world approach to gaining actionable insights from your data /: a practical real-world approach to gaining actionable insights from your data. (2016)
- Record Type:
- Book
- Title:
- Text analytics with Python : a practical real-world approach to gaining actionable insights from your data /: a practical real-world approach to gaining actionable insights from your data. (2016)
- Main Title:
- Text analytics with Python : a practical real-world approach to gaining actionable insights from your data
- Further Information:
- Note: Dipanjan Sarkar.
- Authors:
- Sarkar, Dipanjan
- Contents:
- At 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. PolysemesCapitonyms; 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. Getting 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 SyntaxAt 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. PolysemesCapitonyms; 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. Getting 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. Anonymous 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. Correcting 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? … (more)
- Publisher Details:
- United States : Apress
- Publication Date:
- 2016
- Copyright Date:
- 2016
- Extent:
- 1 online resource
- Subjects:
- 006.3/5
Computer science
Natural language processing (Computer science)
Python (Computer program language)
Programming languages (Electronic computers)
Database management
Data mining
COMPUTERS -- General
Computer science
Data mining
Database management
Natural language processing (Computer science)
Programming languages (Electronic computers)
Python (Computer program language)
Computers -- Database Management -- General
Computers -- Database Management -- Data Mining
Computers -- Programming Languages -- General
Databases
Data mining
Programming & scripting languages: general
Big data
Electronic books
Electronic books - Languages:
- English
- ISBNs:
- 9781484223888
1484223888
9781484223871 - Related ISBNs:
- 148422387X
9781484223871 - Notes:
- Note: Online resource; title from PDF title page (SpringerLink, viewed January 3, 2017).
- Access Rights:
- Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
- Access Usage:
- Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD.DS.359824
- Ingest File:
- 01_322.xml