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Paperback: 544 pages Publisher: Manning Publications; 1st edition (April 14, 2019) Language: English
ISBN-10: 1617294632 ISBN-13: 978-1617294631 Product Dimensions: 7.4 x 1.2 x 9.2 inches Shipping
Weight: 2.1 pounds (View shipping rates and policies)
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Book Description
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. All examples are included in the open source `nlpia` package
on python.org and github.com, complete with a conda environment and Dockerfile to help you get
going quickly on any platform. 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 Authors Hobson Lane,
Cole Howard, and Hannes Max Hapke are experienced NLP engineers who use these techniques
in production for profit and fun: contributing to social-benefit projects like smart guides for
people with blindness and cognitive assistance for those with developmental challenges or
suffering from information overload (don't we all?). Table of Contents PART 1 - WORDY
MACHINES Packets of thought (NLP overview) Build your vocabulary (word tokenization)
Math with words (TF-IDF vectors) Finding meaning in word counts (semantic analysis) PART 2 -
DEEPER LEARNING (NEURAL NETWORKS) Baby steps with neural networks (perceptrons
and backpropagation) Reasoning with word vectors (Word2vec) Getting words in order with
convolutional neural networks (CNNs) Loopy (recurrent) neural networks (RNNs) Improving
retention with long short-term memory networks Sequence-to-sequence models and attention
PART 3 - GETTING REAL (REAL-WORLD NLP CHALLENGES) Information extraction
(named entity extraction and question answering) Getting chatty (dialog engines) Scaling up
(optimization, parallelization, and batch processing)
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