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- Herausgeber: Packt Publishing
- Kategorie: Lebensstil
- Sprache: Englisch
- Veröffentlichungsjahr: 2021
Python is the most widely used language for natural language processing (NLP) thanks to its extensive tools and libraries for analyzing text and extracting computer-usable data. This book will take you through a range of techniques for text processing, from basics such as parsing the parts of speech to complex topics such as topic modeling, text classification, and visualization.
Starting with an overview of NLP, the book presents recipes for dividing text into sentences, stemming and lemmatization, removing stopwords, and parts of speech tagging to help you to prepare your data. You’ll then learn ways of extracting and representing grammatical information, such as dependency parsing and anaphora resolution, discover different ways of representing the semantics using bag-of-words, TF-IDF, word embeddings, and BERT, and develop skills for text classification using keywords, SVMs, LSTMs, and other techniques. As you advance, you’ll also see how to extract information from text, implement unsupervised and supervised techniques for topic modeling, and perform topic modeling of short texts, such as tweets. Additionally, the book shows you how to develop chatbots using NLTK and Rasa and visualize text data.
By the end of this NLP book, you’ll have developed the skills to use a powerful set of tools for text processing.
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Python Natural Language Processing Cookbook
Over 50 recipes to understand, analyze, and generate text for implementing language processing tasks
Zhenya Antić
BIRMINGHAM—MUMBAI
Python Natural Language Processing Cookbook
Copyright © 2021 Packt Publishing
All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.
Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the author, nor Packt Publishing or its dealers and distributors, will be held liable for any damages caused or alleged to have been caused directly or indirectly by this book.
Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.
Group Product Manager: Kunal Parikh
Publishing Product Manager: Aditi Gour
Senior Editor: Mohammed Yusuf Imaratwale
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First published: March 2021
Production reference: 2220421
Published by Packt Publishing Ltd.
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ISBN 978-1-83898-731-2
www.packt.com
Contributors
About the author
Zhenya Antić is a Natural Language Processing (NLP) professional working at Practical Linguistics Inc. She helps businesses to improve processes and increase productivity by automating text processing. Zhenya holds a PhD in linguistics from University of California Berkeley and a BS in computer science from Massachusetts Institute of Technology.
I would like to thank those who helped this book come to life. The whole Packt team, including Ali Abidi, Gebin George, Nazia Shaikh, Aayan Hoda, Steffie Rodrigues and Pooja Yadav, has been really helpful, providing insight and tips when necessary.
I would also like to thank all the technical reviewers, including Mayank Rasu and Dylan Vivier, as well as Vera Gor, for their insightful comments about the code.
A special thanks goes to Miloš Babić, who reviewed the whole book, and Andjelka Zečević, who reviewed the deep learning sections. They provided very useful feedback.
Finally, I would like to thank my family for their constant support.
About the reviewers
Mayank Rasu is the author of the book Hands-On Natural Language Processing with Python. He has more than 12 years of global experience as a data scientist and quantitative analyst in the investment banking domain. He has worked at the intersection of finance and technology and has developed and deployed AI-based applications in the finance domain, which include sentiment analyzer, robotics process automation, and deep learning-based document reviewers. Mayank is also an educator and has trained/mentored working professionals on applied AI.
Dylan Vivier is a data science enthusiast with experience in the automotive, oil and gas, and shipbuilding industries. With engineering degrees from both the University of Detroit and Purdue University, he has also studied at the Indiana University Luddy School of Informatics, Computing, and Engineering. In his spare time, Dylan enjoys researching new applications for data science and playing chess. Diversity and inclusion, Agile project development, Python, SQL, algorithms, data structures, Condition-based Maintenance (CBM), cybersecurity, machine learning, Natural Language Processing (NLP), Internet of Things (IoT), AI, and Blockchain are some of his other interests.
