Natural Language Processing in Action, Second Edition - (In Action) 2nd Edition by Hobson Lane & Maria Dyshel (Paperback)

About the Book

Develop your NLP skills from scratch! This revised bestseller now includes coverage of the latest Python packages, Transformers, the HuggingFace packages, and chatbot frameworks.Natural Language Processing in Action has helped thousands of data scientists build machines that understand human language. In this new and revised edition, you'll discover state-of-the art NLP models like BERT and HuggingFace transformers, popular open-source frameworks for chatbots, and more. As you go, you'll create projects that can detect fake news, filter spam, and even answer your questions, all built with Python and its ecosystem of data tools.
Natural Language Processing in Action, Second Edition is your guide to building software that can read and interpret human language. This new edition is updated to include the latest Python packages and comes with full coverage of cutting-edge models like BERT, GPT-J and HuggingFace transformers.In it, you'll learn to create fun and useful NLP applications such as semantic search engines that are even better than Google, chatbots that can help you write a book, and a multilingual translation program. Soon, you'll be ready to start tackling real-world problems with NLP.

Book Synopsis

Develop your NLP skills from scratch, with an open source toolbox of Python packages, Transformers, Hugging Face, vector databases, and your own Large Language Models.

Natural Language Processing in Action, Second Edition has helped thousands of data scientists build machines that understand human language. In this new and revised edition, you'll discover state-of-the art Natural Language Processing (NLP) models like BERT and HuggingFace transformers, popular open-source frameworks for chatbots, and more. You'll create NLP tools that can detect fake news, filter spam, deliver exceptional search results and even build truthfulness and reasoning into Large Language Models (LLMs).

In Natural Language Processing in Action, Second Edition you will learn how to:

- Process, analyze, understand, and generate natural language text
- Build production-quality NLP pipelines with spaCy
- Build neural networks for NLP using Pytorch
- BERT and GPT transformers for English composition, writing code, and even organizing your thoughts
- Create chatbots and other conversational AI agents

In this new and revised edition, you'll discover state-of-the art NLP models like BERT and HuggingFace transformers, popular open-source frameworks for chatbots, and more. Plus, you'll discover vital skills and techniques for optimizing LLMs including conversational design, and automating the "trial and error" of LLM interactions for effective and accurate results.

Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.

About the technology

From nearly human chatbots to ultra-personalized business reports to AI-generated email, news stories, and novels, natural language processing (NLP) has never been more powerful! Groundbreaking advances in deep learning have made high-quality open source models and powerful NLP tools like spaCy and PyTorch widely available and ready for production applications. This book is your entrance ticket--and backstage pass--into the next generation of natural language processing.

About the book

Natural Language Processing in Action, Second Edition introduces the foundational technologies and state-of-the-art tools you'll need to write and publish NLP applications. You learn how to create custom models for search, translation, writing assistants, and more, without relying on big commercial foundation models. This fully updated second edition includes coverage of BERT, Hugging Face transformers, fine-tuning large language models, and more.

What's inside

- NLP pipelines with spaCy
- Neural networks with PyTorch
- BERT and GPT transformers
- Conversational design for chatbots

About the reader

For intermediate Python programmers familiar with deep learning basics.

About the author

Hobson Lane is a data scientist and machine learning engineer with over twenty years of experience building autonomous systems and NLP pipelines. Maria Dyshel is a social entrepreneur and artificial intelligence expert, and the CEO and cofounder of Tangible AI.

Cole Howard and Hannes Max Hapke were co-authors of the first edition.

Table fo Contents

Part 1
1 Machines that read and write: A natural language processing overview
2 Tokens of thought: Natural language words
3 Math with words: Term frequency-inverse document frequency vectors
4 Finding meaning in word counts: Semantic analysis
Part 2
5 Word brain: Neural networks
6 Reasoning with word embeddings
7 Finding kernels of knowledge in text with CNNs
8 Reduce, reuse, and recycle your words: RNNs and LSTMs
Part 3
9 Stackable deep learning: Transformers
10 Large language models in the real world
11 Information extraction and knowledge graphs
12 Getting chatty with dialog engines
A Your NLP tools
B Playful Python and regular expressions
C Vectors and linear algebra
D Machine learning tools and techniques
E Deploying NLU containerized microservices
F Glossary

From the Back Cover

Develop your NLP skills from scratch! This revised bestseller now includes coverage of the latest Python packages, Transformers, the HuggingFace packages, and chatbot frameworks.In Natural Language Processing in Action, Second Edition you will learn how to:

Process, analyze, understand, and generate natural language text Build production-quality NLP pipelines with spaCy Build neural networks for NLP using Pytorch BERT and GPT transformers for English composition, writing code, and even organizing your thoughts Create chatbots and other conversational AI agents

Natural Language Processing in Action has helped thousands of data scientists build machines that understand human language. In this new and revised edition, you'll discover state-of-the art NLP models like BERT and HuggingFace transformers, popular open-source frameworks for chatbots, and more. As you go, you'll create projects that can detect fake news, filter spam, and even answer your questions, all built with Python and its ecosystem of data tools.
Deep learning has been a giant leap forward for NLP applications. Developers can now build chatbots and other natural language tools that can imitate real people, diagnose illness, automatically summarize documents, and more. Accessible open source tools such as spaCy and PyTorch make production-level NLP easier and more impactful than ever before.

About the Author

Hobson Lane is a data scientist and machine learning engineer. He has over twenty years experience building autonomous systems and NLP pipelines for both large corporations and startups. Currently, Hobson is an instructor at UCSD Extension and Springboard, and the CTO and cofounder of Tangible AI and ProAI.org.

Maria Dyshel is a social entrepreneur and artificial intelligence expert. She held a variety of AI research, engineering, and management roles in diverse industries, from designing and improving algorithms for autonomous vehicles, to implementing company-wide Conversational AI program in one of the world's largest pharma companies. Maria is currently the CEO and cofounder of Tangible AI.