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Natural Language Processing in Action

Natural Language Processing in Action

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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. AUTHOR BIO 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 start-ups. 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.

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About the Book

Summary

Natural Language Processing in Action is your guide to creating machines that understand human language using the power of Python with its ecosystem of packages dedicated to NLP and AI.

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

About the Technology

Recent advances in deep learning empower applications to understand text and speech with extreme accuracy. The result? Chatbots that can imitate real people, meaningful resume-to-job matches, superb predictive search, and automatically generated document summaries--all at a low cost. New techniques, along with accessible tools like Keras and TensorFlow, make professional-quality NLP easier than ever before.

About the Book

Natural Language Processing in Action is your guide to building machines that can read and interpret human language. In it, you'll use readily available Python packages to capture the meaning in text and react accordingly. The book expands traditional NLP approaches to include neural networks, modern deep learning algorithms, and generative techniques as you tackle real-world problems like extracting dates and names, composing text, and answering free-form questions.

What's inside

  • Some sentences in this book were written by NLP! Can you guess which ones?
  • Working with Keras, TensorFlow, gensim, and scikit-learn
  • Rule-based and data-based NLP
  • Scalable pipelines

About the Reader

This book requires a basic understanding of deep learning and intermediate Python skills.

About the Author

Hobson Lane, Cole Howard, and Hannes Max Hapke are experienced NLP engineers who use these techniques in production.

Table of Contents

    PART 1 - WORDY MACHINES
  1. Packets of thought (NLP overview)
  2. Build your vocabulary (word tokenization)
  3. Math with words (TF-IDF vectors)
  4. Finding meaning in word counts (semantic analysis)
  5. PART 2 - DEEPER LEARNING (NEURAL NETWORKS)
  6. Baby steps with neural networks (perceptrons and backpropagation)
  7. Reasoning with word vectors (Word2vec)
  8. Getting words in order with convolutional neural networks (CNNs)
  9. Loopy (recurrent) neural networks (RNNs)
  10. Improving retention with long short-term memory networks
  11. Sequence-to-sequence models and attention
  12. PART 3 - GETTING REAL (REAL-WORLD NLP CHALLENGES)
  13. Information extraction (named entity extraction and question answering)
  14. Getting chatty (dialog engines)
  15. Scaling up (optimization, parallelization, and batch processing)


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Product Details
  • ISBN-13: 9781617294631
  • Publisher: Manning Publications
  • Publisher Imprint: Manning Publications
  • Depth: 22
  • Language: English
  • Returnable: Y
  • Sub Title: Understanding, Analyzing, and Generating Text with Python
  • Width: 235 mm
  • ISBN-10: 1617294632
  • Publisher Date: 14 Apr 2019
  • Binding: Paperback
  • Height: 191 mm
  • No of Pages: 544
  • Spine Width: 35 mm
  • Weight: 1002 gr


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