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Practical Natural Language Processing with Python - With Case Studies from Industries Using Text Data at Scale (Paperback, 1st ed.)
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Practical Natural Language Processing with Python - With Case Studies from Industries Using Text Data at Scale (Paperback, 1st ed.)
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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. What You Will Learn 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 Who This Book Is For Analytics and
data science professionals who want to kick start NLP, and NLP
professionals who want to get new ideas to solve the problems at
hand.
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