Natural Language Processing with Python and spaCy: A Practical Introduction


Natural Language Processing with Python and spaCy: A Practical Introduction
By 作者: Yuli Vasiliev
pages 页数: 216 pages
Edition 版本: 1
Language 语言: English
Publisher Finelybook 出版社: No Starch Press
Publication Date 出版日期: 2020-04-21
ISBN-10 书号:1718500521
ISBN-13 书号:9781718500525
Book Description to Finelybook sorting
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.

BRIEF CONTENTS
CONTENTS IN DETAIL
INTRODUCTION
1 HOW NATURAL LANGUAGE PROCESSING WORKS
2 THE TEXT-PROCESSING PIPELINE
3 WORKING WITH CONTAINER OBJECTS AND CUSTOMIZING SPACY
4 EXTRACTING AND USING LINGUISTIC FEATURES
5 WORKING WITH WORD VECTORS
6 FINDING PATTERNS AND WALKING DEPENDENCY TREES
7 VISUALIZATIONS
8 INTENT RECOGNITION
9 STORING USER INPUT IN A DATABASE
10 TRAINING MODELS
11 DEPLOYING YOUR OWN CHATBOT
12IMPLEMENTING WEB DATA AND PROCESSING IMAGES
LINGUISTIC PRIMER
INDEX


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