Text Analytics with Python (e-bog) af Sarkar, Dipanjan
Sarkar, Dipanjan (forfatter)

Text Analytics with Python e-bog

403,64 DKK (inkl. moms 504,55 DKK)
Derive useful insights from your data using Python. You will learn both basic and advanced concepts, including text and language syntax, structure, and semantics. You will focus on algorithms and techniques, such as text classification, clustering, topic modeling, and text summarization.Text Analytics with Python teaches you the techniques related to natural language processing and text an...
E-bog 403,64 DKK
Forfattere Sarkar, Dipanjan (forfatter)
Forlag Apress
Udgivet 30 november 2016
Genrer UMC
Sprog English
Format pdf
Beskyttelse LCP
ISBN 9781484223888
Derive useful insights from your data using Python. You will learn both basic and advanced concepts, including text and language syntax, structure, and semantics. You will focus on algorithms and techniques, such as text classification, clustering, topic modeling, and text summarization.Text Analytics with Python teaches you the techniques related to natural language processing and text analytics, and you will gain the skills to know which technique is best suited to solve a particular problem. 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.What You Will Learn:Understand the major concepts and techniques of natural language processing (NLP) and text analytics, including syntax and structureBuild a text classification system to categorize news articles, analyze app or game reviews using topic modeling and text summarization, and cluster popular movie synopses and analyze the sentiment of movie reviewsImplement Python and popular open source libraries in NLP and text analytics, such as the natural language toolkit (nltk), gensim, scikit-learn, spaCy and PatternWho This Book Is For :IT professionals, analysts, developers, linguistic experts, data scientists, and anyone with a keen interest in linguistics, analytics, and generating insights from textual data