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Natural Language Processing in Action, Second Edition de Hobson Lane

Natural Language Processing in Action, Second Edition

Autor Hobson Lane, Maria Dyshel
en Limba Engleză Paperback – 25 feb 2025

Observăm că Natural Language Processing in Action, Second Edition este concepută pentru inginerii de date și dezvoltatorii care posedă deja o bază solidă în Python și doresc să treacă de la manipularea simplă a textului la sisteme capabile să înțeleagă contextul uman. Cartea presupune o familiaritate cu conceptele de programare și o înțelegere elementară a structurilor de date, fiind un ghid tehnic riguros publicat de Manning Publications. Ca și Ankur A Patel în Applied Natural Language Processing in the Enterprise, autorii Hobson Lane și Maria Dyshel distilează experiență reală în principii acționabile, punând accent pe implementări care pot fi livrate în producție. Structura este progresivă și logică: prima parte introduce cititorul în modelele vectoriale și analiza semantică (TF-IDF), partea a doua explorează profunzimea rețelelor neuronale (CNN, RNN, LSTM și mecanisme de atenție), iar ultima parte se concentrează pe provocările practice, precum extragerea de informații și scalarea sistemelor prin paralelizare. Apreciem în mod deosebit modul în care această a doua ediție integrează tehnologii care au revoluționat domeniul recent, cum sunt modelele Transformer (BERT, GPT-J). Cititorul nu primește doar teorie; cuprinsul indică o trecere rapidă spre aplicații complexe: de la motoare de căutare semantică superioare soluțiilor comerciale standard, până la motoare de dialog și traducere multilingvă. Tonul este pragmatic, axat pe rezolvarea problemelor de performanță și optimizarea resurselor, transformând concepte matematice abstracte în instrumente software funcționale.

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Specificații

ISBN-13: 9781617299445
ISBN-10: 1617299448
Pagini: 688
Dimensiuni: 190 x 233 x 42 mm
Greutate: 1.15 kg
Ediția:2nd edition
Editura: Manning Publications

De ce să citești această carte

Recomandăm această carte dezvoltatorilor care vor să stăpânească ecosistemul modern de NLP, trecând dincolo de simple biblioteci de procesare a textului. Veți câștiga competențe practice în lucrul cu Transformers și HuggingFace, învățând să construiți aplicații scalabile, de la chatbot-uri la sisteme de detecție a știrilor false. Este o investiție esențială pentru a rămâne relevanți într-un domeniu care evoluează accelerat spre modele generative.

Descriere scurtă

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.

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

Cuprins

table of contents
PART 1: WORDY MACHINES (VECTOR MODELS OF NATURAL LANGUAGE)
READ IN LIVEBOOK1MACHINES THAT READ AND WRITE (NLP OVERVIEW)
READ IN LIVEBOOK2TOKENS OF THOUGHT (NATURAL LANGUAGE WORDS)
READ IN LIVEBOOK3MATH WITH WORDS (TF-IDF VECTORS)
READ IN LIVEBOOK4FINDING 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

Notă biografică

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.