Natural Language Processing in Action: Understanding, analyzing, and generating text with Python

Natural Language Processing in Action: Understanding, analyzing, and generating text with Python

SummaryNatural 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 TechnologyRecent 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 BookNatural 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 insideSome sentences in this book were written by NLP! Can you guess which ones?Working with Keras, TensorFlow, gensim, and scikit-learnRule-based and data-based NLPScalable pipelinesAbout the ReaderThis book requires a basic understanding of deep learning and intermediate Python skills.About the AuthorHobson Lane, Cole Howard, and Hannes Max Hapke are experienced NLP engineers who use these techniques in production.Table of ContentsPART 1 – WORDY MACHINESPackets 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 networksSequence-to-sequence models and attentionPART 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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Editorial Reviews

About the Author

Hobson Lane has more than 15 years of experience building autonomous systems that make important decisions on behalf of humans.

Hannes Hapke is an Electrical Engineer turned Data Scientist with experience in deep learning.

Cole Howard is a carpenter and writer turned Deep Learning expert.

–This text refers to an alternate kindle_edition edition.


“Learn both the theory and practical skills needed to go beyond merely understanding the inner workings of NLP, and start creating your own algorithms or models.”–From the Foreword by Dr. Arwen Griffioen, Zendesk

“Provides a great overview of current NLP tools in Python. I’ll definitely be keeping this book on hand for my own NLP work. Highly recommended!”–Tony Mullen, Northeastern University-Seattle

“An intuitive guide to get you started with NLP. The book is full of programming examples that help you learn in a very pragmatic way.”–Tommaso Teofili, Adobe Systems

–This text refers to an alternate kindle_edition edition.

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#358,510 in Kindle Store (See Top 100 in Kindle Store) #15 in Voice Recognition Software #25 in Natural Language Processing (Kindle Store) #41 in C++ Programming

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