Natural Language Processing Fundamentals for Developers / / Oswald Campesato.

This book is for developers who are looking for an overview of basic concepts in Natural Language Processing. It casts a wide net of techniques to help developers who have a range of technical backgrounds. Numerous code samples and listings are included to support myriad topics. The first chapter sh...

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Place / Publishing House:Dulles, VA : : Mercury Learning and Information, , [2021]
©2021
Year of Publication:2021
Language:English
Online Access:
Physical Description:1 online resource (364 p.)
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245 1 0 |a Natural Language Processing Fundamentals for Developers /  |c Oswald Campesato. 
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300 |a 1 online resource (364 p.) 
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505 0 0 |t Frontmatter --   |t Contents --   |t Preface --   |t Chapter 1: Working with Data --   |t Chapter 2: NLP Concepts (I) --   |t Chapter 3: NLP Concepts (II) --   |t Chapter 4: Algorithms and Toolkits (I) --   |t Chapter 5: Algorithms and Toolkits (II) --   |t Chapter 6: NLP Applications --   |t Chapter 7: Transformer, BERT, and GPT --   |t Appendix A: Introduction to Regular Expressions --   |t Appendix B: Introduction to Probability and Statistics --   |t Index 
506 0 |a restricted access  |u http://purl.org/coar/access_right/c_16ec  |f online access with authorization  |2 star 
520 |a This book is for developers who are looking for an overview of basic concepts in Natural Language Processing. It casts a wide net of techniques to help developers who have a range of technical backgrounds. Numerous code samples and listings are included to support myriad topics. The first chapter shows you various details of managing data that are relevant for NLP. The next pair of chapters contain NLP concepts, followed by another pair of chapters with Python code samples to illustrate those NLP concepts. Chapter 6 explores applications, e.g., sentiment analysis, recommender systems, COVID-19 analysis, spam detection, and a short discussion regarding chatbots. The final chapter presents the Transformer architecture, BERT-based models, and the GPT family of models, all of which were developed during the past three years and considered SOTA (“state of the art”). The appendices contain introductory material (including Python code samples) on regular expressions and probability/statistical concepts. Companion files with source code and figures are included.FEATURES:Covers extensive topics related to natural language processing Includes separate appendices on regular expressions and probability/statisticsFeatures companion files with source code and figures from the book.The companion files are available online by emailing the publisher with proof of purchase at info@merclearning.com. 
530 |a Issued also in print. 
538 |a Mode of access: Internet via World Wide Web. 
546 |a In English. 
588 0 |a Description based on online resource; title from PDF title page (publisher's Web site, viewed 08. Aug 2023) 
650 4 |a Data. 
650 7 |a COMPUTERS / Natural Language Processing.  |2 bisacsh 
653 |a Computer Science. 
653 |a Data Analytics. 
653 |a Machine Learning. 
653 |a Natural Language Processing. 
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