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020 1484262468
020 9781484262467
024 7 10.1007/978-1-4842-6246-7.|2doi
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082 04 006.31
082 04 006.31|223
099 eBook O'Reilly for Public Libraries
100 1 Sri, Mathangi.,|eauthor.|4aut|4http://id.loc.gov/
vocabulary/relators/aut
245 10 Practical Natural Language Processing with Python
|h[electronic resource] :|bWith Case Studies from
Industries Using Text Data at Scale /|cby Mathangi Sri.
|h[O'Reilly electronic resource]
250 1st ed. 2021.
264 1 Berkeley, CA :|bApress :|bImprint: Apress,|c2021.
300 1 online resource (XV, 253 p. 103 illus.)
336 text|btxt|2rdacontent
337 computer|bc|2rdamedia
338 online resource|bcr|2rdacarrier
347 text file|bPDF|2rda
490 0 ITpro collection
504 Includes bibliographical references.
505 0 Chapter 1: Text Data in Real Word -- Chapter 2: NLP in
Customer Service -- Chapter 3: NLP in Online Reviews --
Chapter 4: NLP in BFSI -- Chapter 5: NLP in Virtual
Assistants.
520 Work with natural language tools and techniques to solve
real-world problems. This book focuses on how natural
language processing (NLP) is used in various industries.
Each chapter describes the problem and solution strategy,
then provides an intuitive explanation of how different
algorithms work and a deeper dive on code and output in
Python. Practical Natural Language Processing with Python
follows a case study-based approach. Each chapter is
devoted to an industry or a use case, where you address
the real business problems in that industry and the
various ways to solve them. You start with various types
of text data before focusing on the customer service
industry, the type of data available in that domain, and
the common NLP problems encountered. Here you cover the
bag-of-words model supervised learning technique as you
try to solve the case studies. Similar depth is given to
other use cases such as online reviews, bots, finance, and
so on. As you cover the problems in these industries
you'll also cover sentiment analysis, named entity
recognition, word2vec, word similarities, topic modeling,
deep learning, and sequence to sequence modelling. By the
end of the book, you will be able to handle all types of
NLP problems independently. You will also be able to think
in different ways to solve language problems. Code and
techniques for all the problems are provided in the book.
You will: Build an understanding of NLP problems in
industry Gain the know-how to solve a typical NLP problem
using language-based models and machine learning Discover
the best methods to solve a business problem using NLP -
the tried and tested ones Understand the business problems
that are tough to solve .
590 O'Reilly|bO'Reilly Online Learning: Academic/Public
Library Edition
650 0 Machine learning.
650 0 Python (Computer program language)
650 0 Open source software.
650 0 Computer programming.
650 2 Machine Learning
650 6 Apprentissage automatique.
650 6 Python (Langage de programmation)
650 6 Logiciels libres.
650 6 Programmation (Informatique)
650 7 computer programming.|2aat
650 7 Computer programming|2fast
650 7 Machine learning|2fast
650 7 Open source software|2fast
650 7 Python (Computer program language)|2fast
650 14 Machine Learning.|0https://scigraph.springernature.com/
ontologies/product-market-codes/I21010
650 22 Boidae
650 24 Python.|0https://scigraph.springernature.com/ontologies/
product-market-codes/I29080
650 24 Open Source.|0https://scigraph.springernature.com/
ontologies/product-market-codes/I29090
776 |z1-4842-6245-X
856 40 |uhttps://ezproxy.naperville-lib.org/login?url=https://
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|aAvailable on O'Reilly for Public Libraries
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994 92|bJFN