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[EBOOK] Natural Language Processing in Action: Understanding, analyzing, and generating text with Python *Full Online

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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

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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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