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Natural Language Processing in Action, Second Edition
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
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.
Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.
About the technology
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 book
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.
About the reader
This book requires a basic understanding of deep learning and intermediate Python skills.
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.
Cole Howard and Hannes Max Hapke were authors of the first edition of Natural Language Processing in Action and their legacy lives on in the collective intelligence of the community around the book.
In Natural Language Processing in Action, Second Edition you will learn how
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.
Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.
About the technology
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 book
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.
About the reader
This book requires a basic understanding of deep learning and intermediate Python skills.
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.
Cole Howard and Hannes Max Hapke were authors of the first edition of Natural Language Processing in Action and their legacy lives on in the collective intelligence of the community around the book.
- GenresArtificial Intelligence
688 pages, Paperback
Published February 25, 2025
8 people are currently reading
25 people want to read
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Displaying 1 - 3 of 3 reviews
February 27, 2025
The second edition of Natural Language Processing in Action by Hobson Lane and Maria Dyshel is a valuable resource for anyone looking to master NLP. Building on the strengths of the first edition, this updated version introduces cutting-edge techniques while maintaining its hands-on, accessible approach. Whether you're a data scientist, AI researcher, or software engineer, this book is an invaluable guide to building practical NLP solutions using Python.
The second edition significantly expands on the original by incorporating recent advancements in NLP, particularly in deep learning and transformer models. Some major enhancements include:
• Expanded Coverage of Transformers – While the first edition introduced basic neural networks, this edition provides an in-depth look at state-of-the-art models like BERT, GPT, and T5, with practical implementations.
• More Hands-On Projects – This edition places even greater emphasis on real-world applications, offering projects such as semantic search engines, text classification, and multilingual translation.
• Integration with Modern Libraries – The first edition focused on foundational NLP with TensorFlow and scikit-learn, whereas the second edition updates the tech stack to include PyTorch and spaCy, ensuring compatibility with the latest industry trends.
• Conversational AI Development – Unlike the previous edition, this book dedicates a full section to chatbot development, covering dialogue management, response generation, and real-world deployment strategies.
In particular the following chapters stood out for me:
• Introduction to NLP Pipelines – This foundational chapter sets the stage by explaining tokenization, stemming, and lemmatization using spaCy, making it easier for newcomers to grasp core concepts.
• Building Neural Networks for NLP – Readers are guided through creating deep learning models with PyTorch, bridging the gap between traditional machine learning and modern AI techniques.
• Transformers and Transfer Learning – This is one of the most valuable chapters, as it walks through implementing cutting-edge transformer models, a topic that was only briefly touched upon in the first edition.
• Conversational AI and Chatbots – A brand-new addition, this chapter provides a roadmap for building interactive AI-driven assistants using open-source tools.
• Deploying NLP Models – Unlike the first edition, which focused mostly on model training, this chapter emphasizes real-world deployment strategies using cloud services and APIs.
What makes the second edition of Natural Language Processing in Action stand out is its ability to balance theory with practice. The authors' expertise shines through in their clear explanations, step-by-step code examples, and engaging writing style. With its inclusion of transformers, conversational AI, and modern NLP frameworks, it is undoubtedly one of the best resources for mastering natural language processing today. Whether you're just starting out or looking to advance your expertise, this book will be a valuable addition to your library.
The second edition significantly expands on the original by incorporating recent advancements in NLP, particularly in deep learning and transformer models. Some major enhancements include:
• Expanded Coverage of Transformers – While the first edition introduced basic neural networks, this edition provides an in-depth look at state-of-the-art models like BERT, GPT, and T5, with practical implementations.
• More Hands-On Projects – This edition places even greater emphasis on real-world applications, offering projects such as semantic search engines, text classification, and multilingual translation.
• Integration with Modern Libraries – The first edition focused on foundational NLP with TensorFlow and scikit-learn, whereas the second edition updates the tech stack to include PyTorch and spaCy, ensuring compatibility with the latest industry trends.
• Conversational AI Development – Unlike the previous edition, this book dedicates a full section to chatbot development, covering dialogue management, response generation, and real-world deployment strategies.
In particular the following chapters stood out for me:
• Introduction to NLP Pipelines – This foundational chapter sets the stage by explaining tokenization, stemming, and lemmatization using spaCy, making it easier for newcomers to grasp core concepts.
• Building Neural Networks for NLP – Readers are guided through creating deep learning models with PyTorch, bridging the gap between traditional machine learning and modern AI techniques.
• Transformers and Transfer Learning – This is one of the most valuable chapters, as it walks through implementing cutting-edge transformer models, a topic that was only briefly touched upon in the first edition.
• Conversational AI and Chatbots – A brand-new addition, this chapter provides a roadmap for building interactive AI-driven assistants using open-source tools.
• Deploying NLP Models – Unlike the first edition, which focused mostly on model training, this chapter emphasizes real-world deployment strategies using cloud services and APIs.
What makes the second edition of Natural Language Processing in Action stand out is its ability to balance theory with practice. The authors' expertise shines through in their clear explanations, step-by-step code examples, and engaging writing style. With its inclusion of transformers, conversational AI, and modern NLP frameworks, it is undoubtedly one of the best resources for mastering natural language processing today. Whether you're just starting out or looking to advance your expertise, this book will be a valuable addition to your library.
May 27, 2025
...Unlike a programming language, where each keyword has an unambiguous interpretation, natural languages are much more fuzzy. Think about the sentence, “The chicken is ready to eat.” This could mean that a live chicken is about to eat its breakfast—or that a cooked chicken is ready in the oven. This fuzziness of natural language leaves the interpretation of each word open to you and introduces interesting challenges in understanding and generating human language...
March 18, 2025
This book is great for both beginners and experienced ( NLP experts ) learners. It explains topics like preprocessing, TF-IDF, LDA, LSA, CNN, RNN, LSTM, and Attention in a clear and easy way. After each explanation, there are code examples to help us understand concepts better. Author uses real-life examples to show how the concepts work.
Yet to finish the book , will update the review(detailed review) once I finish the book.
Yet to finish the book , will update the review(detailed review) once I finish the book.
Displaying 1 - 3 of 3 reviews