Natural Language Processing With PyTorch (Color/E)
SKU: 71962619081

Natural Language Processing With PyTorch (Color/E)

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Description

Natural Language Processing With PyTorch (Color/E)Natural Language Processing (NLP) provides boundless opportunities for solving problems in artificial intelligence, making products such as Amazon Alexa and Google Translate possible. If youre a developer or data scientist new to NLP and deep learning, this practical guide shows you how to apply these methods using PyTorch, a Python based deep learning library.' webkit tap highlight color: transparent; color: rgb(102, 102, 102); font family: "Open

Natural Language Processing (NLP) provides boundless opportunities for solving problems in artificial intelligence, making products such as Amazon Alexa and Google Translate possible. If youre a developer or data scientist new to NLP and deep learning, this practical guide shows you how to apply these methods using PyTorch, a Python-based deep learning library.'-webkit-tap-highlight-color: transparent; color: rgb(102, 102, 102); font-family: "Open Sans"; font-size: 13px; margin-top: 0px; margin-bottom: 0px; padding: 6px 0px; background-color: rgb(255, 255, 255);'Authors Delip Rao and Brian McMahon provide you with a solid grounding in NLP and deep learning algorithms and demonstrate how to use PyTorch to build applications involving rich representations of text specific to the problems you face. Each chapter includes several code examples and illustrations.
Explore computational graphs and the supervised learning paradigm
Master the basics of the PyTorch optimized tensor manipulation library
Get an overview of traditional NLP concepts and methods
Learn the basic ideas involved in building neural networks
Use embeddings to represent words, sentences, documents, and other features
Explore sequence prediction and generate sequence-to-sequence models
Learn design patterns for building production NLP systems

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SKU: 71962619081

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Wil C
San Leandro, US
★★★★★ 5
Excellent roadmap for the local AI jungle
Format: Paperback
Great little book. Every page has something useful. No fluff. Clearly written by someone whose been in the trenches lol
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Reviewed in the United States on September 23, 2025
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Abdul
West Palm Beach, US
★★★★★ 5
Great primer for building LLM Applications
Format: Kindle
I highly recommend the book for anyone who wants to come up to speed on running Ollama for open models. The book is well structure and teach you how to create a working RAG Application. I recommend as a primer for anyone interested in building LLM Applications.
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Reviewed in the United States on May 5, 2025
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Y. Banga
Grantham, US
★★★★★ 5
Breaks down complex concepts into bite-sized, practical chapters.
Format: Kindle
This hands-on guide to Ollama is exactly what I needed! The author breaks down complex concepts into bite-sized, practical chapters that get straight to the point. The sections on different Ollama models and customization were particularly helpful. If you're looking to learn about building local LLM-powered applications without any fluff, this book is a great investment.
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Reviewed in the United States on February 21, 2025
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William L. Crupi
Phoenix, US
★★★★★ 5
Great helpful book.
Format: Kindle
This book is simple to follow, Greg gets back to you in a very timely manner. I have bought other books from Greg and they are always very helpful.
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Reviewed in the United States on February 21, 2025
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jeff s kittrell
Phoenix, US
★★★★★ 5
Love it - revolutionary approach to teaching, presenting complex concepts
Format: Paperback
This book is a game-changer for neural networks and AI enthusiasts. It takes a revolutionary approach to teaching, presenting complex concepts in a simple and engaging manner. The book is filled with colorful diagrams and illustrations that make learning accessible and enjoyable. I’ve read several other books, but this one stands out. It’s not a beginner’s guide, but once you grasp the early concepts, it takes you to a whole new level of understanding. I will give it 10 stars if I could.
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Reviewed in the United States on June 18, 2025

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