Natural Language Processing in Action
Paperback Engels 2025 2e druk 9781617299445Samenvatting
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.
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.
Specificaties
Lezersrecensies
Inhoudsopgave
1 MACHINES THAT READ AND WRITE (NLP OVERVIEW)
2 TOKENS OF THOUGHT (NATURAL LANGUAGE WORDS)
3 MATH WITH WORDS (TF-IDF VECTORS)
4 FINDING MEANING IN WORD COUNTS (SEMANTIC ANALYSIS)
PART 2: DEEPER LEARNING (NEURAL NETWORKS)
5 BABY STEPS WITH NEURAL NETWORKS (PERCEPTRONS AND BACKPROPAGATION)
6 REASONING WITH WORD VECTORS (WORD2VEC)
7 GETTING WORDS IN ORDER WITH CONVOLUTIONAL NEURAL NETWORKS (CNNS)
8 LOOPY (RECURRENT) NEURAL NETWORKS (RNNS)
9 IMPROVING RETENTION WITH LONG SHORT-TERM MEMORY NETWORKS (LSTMS)
10 SEQUENCE TO SEQUENCE MODELS AND ATTENTION (GENERATIVE MODELS)
PART 3: GETTING REAL (REAL WORLD NLP CHALLENGES)
11 INFORMATION EXTRACTION (NAMED ENTITY EXTRACTION AND QUESTION ANSWERING)
12 GETTING CHATTY (DIALOG ENGINES)
13 SCALING UP (OPTIMIZATION, PARALLELIZATION AND BATCH POCESSING)
APPENDICES
APPENDIX A: YOUR NLP TOOLS
APPENDIX B: PLAYFUL PYTHON AND REGULAR EXPRESSIONS
APPENDIX C: VECTORS AND MATRICES (BASIC LINEAR ALGEBRA)
APPENDIX D: MACHINE LEARNING
APPENDIX E: AWS GPU
APPENDIX F: LOCALITY SENSITIVE HASHING
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