Natural Language Processing with Python and spaCy: A Practical Introduction
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Description
An introduction to natural language processing with Python using spaCy, a leading Python natural language processing library.Natural Language Processing with Python and spaCy will show you how to create NLP applications like chatbots, text-condensing scripts, and order-processing tools quickly and easily. You’ll learn how to leverage the spaCy library to extract meaning from text intelligently; how to determine the relationships between words in a sentence (syntactic dependency parsing); identify nouns, verbs, and other parts of speech (part-of-speech tagging); and sort proper nouns into categories like people, organizations, and locations (named entity recognizing). You’ll even learn how to transform statements into questions to keep a conversation going.You’ll also learn how to:Work with word vectors to mathematically find words with similar meanings (Chapter 5)Identify patterns within data using spaCy’s built-in displaCy visualizer (Chapter 7)Automatically extract keywords from user input and store them in a relational database (Chapter 9)Deploy a chatbot app to interact with users over the internet (Chapter 11)”Try This” sections in each chapter encourage you to practice what you’ve learned by expanding the book’s example scripts to handle a wider range of inputs, add error handling, and build professional-quality applications.By the end of the book, you’ll be creating your own NLP applications with Python and spaCy.
Additional information
Weight | 0.43 kg |
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Dimensions | 1.27 × 17.78 × 4.23 cm |
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Format | Paperback |
Language | |
Pages | 216 |
Publisher | |
Year Published | 2020-5-12 |
Imprint | |
Publication City/Country | USA |
ISBN 10 | 1718500521 |
About The Author | Yuli Vasiliev is a programmer, freelance writer, and consultant who specializes in open source development, Oracle database technologies, and natural language processing. |
"A good resource for those programmers who want to learn to bridge the gap and write applications that anyone can use just by talking or writing to their machines and have the machine reply back." —Jon Lazar, JustJon |
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Table Of Content | IntroductionChapter 1: How Natural Language Processing WorksChapter 2: The Text-Processing PipelineChapter 3: Working with Container Objects and Customizing spaCyChapter 4: Extracting and Using Linguistic FeaturesChapter 5: Working with Word VectorsChapter 6: Finding Patterns and Walking Dependency TreesChapter 7: VisualizationsChapter 8: Intent RecognitionChapter 9: Storing User Input in a DatabaseChapter 10: Training ModelsChapter 11: Deploying Your Own ChatbotChapter 12: Implementing Web Data and Processing ImagesLinguistic Primer |
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