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
Packets of thought
Build your vocabulary
Math with words
Finding meaning in word counts
PART 2 - DEEPER LEARNING
Baby steps with neural networks
Reasoning with word vectors
Getting words in order with convolutional neural networks
Loopy neural networks
Improving retention with long short-term memory networks
Sequence-to-sequence models and attention
PART 3 - GETTING REAL
Information extraction
Getting chatty
Scaling up
Pages
544
Format
ebook
ISBN 13
9781638356899
Natural Language Processing in Action: Understanding, analyzing, and generating text with Python
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
Packets of thought
Build your vocabulary
Math with words
Finding meaning in word counts
PART 2 - DEEPER LEARNING
Baby steps with neural networks
Reasoning with word vectors
Getting words in order with convolutional neural networks
Loopy neural networks
Improving retention with long short-term memory networks
Sequence-to-sequence models and attention
PART 3 - GETTING REAL
Information extraction
Getting chatty
Scaling up