Natural Language Processing Cookbook
eBook - ePub

Natural Language Processing Cookbook

Step-by-step practical solution for unlocking the power of natural language processing potential (English Edition)

  1. English
  2. ePUB (mobile friendly)
  3. Available on iOS & Android
eBook - ePub

Natural Language Processing Cookbook

Step-by-step practical solution for unlocking the power of natural language processing potential (English Edition)

About this book

Description
Natural language processing (NLP) is revolutionizing how machines understand and interact with human language, creating powerful applications from chatbots to text analytics. This provides a practical, hands-on approach to mastering these technologies, making complex NLP concepts accessible through step-by-step recipes and real-world examples.This book walks you through the world of teaching computers to understand human language, starting with the basics and building up to advanced techniques. You will learn how to break down text into meaningful pieces, use Python programming to handle text data, and clean up messy text for analysis. The book shows you how computers can understand the meaning behind words using methods like word embeddings and BERT. You will discover how to identify parts of speech and recognize names of people and places in text, and how to sort text into different categories using ML. Advanced topics include finding hidden themes in document collections, building chatbots that can have conversations, and creating visual representations of text data. Throughout the book, practical Python examples help you implement these techniques while considering how to evaluate and deploy real-world NLP systems.By the time you complete this book, you will possess the technical proficiency to implement complete NLP pipelines from preprocessing to deployment. The recipe-based approach ensures you can immediately apply these techniques to solve real business problems.

Key Features
? Step-by-step approach for each technique, with practical examples to fully master NLP.
? Add value to your data by mastering the most important NLP techniques.
? Readily usable recipes for implementing basic tasks like data cleaning and tokenization to more complicated neural network implementations.

What you will learn
? Preprocess and clean text for accurate NLP model performance.
? Apply ML techniques for text classification tasks.
? Extract key insights using semantic analysis and embeddings.
? Develop and fine-tune topic modeling algorithms.
? Build intelligent chatbots with dialogue management and intent detection.
? Visualize text data with word clouds and entity graphs.

Who this book is for
This book is ideal for data scientists, programmers, business analysts, and students with basic Python knowledge who want to build practical NLP skills. Whether you are an AI enthusiast looking to enter the field or a professional seeking to add language processing capabilities to your toolkit, you will find actionable recipes that bridge theory and application.

Table of Contents
1. Getting Started with NLP
2. Python for Text Processing
3. Text Processing and Cleaning
4. Semantic Representation
5. Part-of-speech Tagging and Named Entity Recognition
6. Text Classification
7. Advanced Techniques for Topic Modeling
8. Building a Chatbot
9. Text Data Visualization Techniques
10. Conclusion and Takeaways

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Yes, you can access Natural Language Processing Cookbook by Rosario Moscato,Alessio Ligios,Corrado Silvestri in PDF and/or ePUB format, as well as other popular books in Computer Science & Artificial Intelligence (AI) & Semantics. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover
  2. Title Page
  3. Copyright Page
  4. Dedication Page
  5. About the Authors
  6. About the Reviewer
  7. Acknowledgements
  8. Preface
  9. Table of Contents
  10. 1. Getting Started with NLP
  11. 2. Python for Text Processing
  12. 3. Text Processing and Cleaning
  13. 4. Semantic Representation
  14. 5. Part-of-speech Tagging and Named Entity Recognition
  15. 6. Text Classification
  16. 7. Advanced Techniques for Topic Modeling
  17. 8. Building a Chatbot
  18. 9. Text Data Visualization Techniques
  19. 10. Conclusion and Takeaways
  20. Index