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Natural Language Processing with PyTorch: Build Intelligent Language Applications Using Deep Learning
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(as of Dec 24,2024 10:45:16 UTC – Details)
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Publisher : O’Reilly Media; 1st edition (March 12, 2019)
Language : English
Paperback : 254 pages
ISBN-10 : 1491978236
ISBN-13 : 978-1491978238
Item Weight : 14.4 ounces
Dimensions : 9.2 x 0.5 x 6.9 inches
Customers say
Customers find this book teaches NLP basics from the ground up, covering the concepts clearly and demonstrating them. They describe it as an awesome book to dive into NLP and deep learning frameworks. However, some readers feel the book is too thin and concise. There are mixed opinions on the code quality, with some finding it well-written and valuable for beginners, while others mention issues with poorly structured code and brief explanations.
AI-generated from the text of customer reviews
Natural Language Processing (NLP) is a rapidly growing field in the world of artificial intelligence, and PyTorch is one of the most popular deep learning frameworks for building intelligent language applications. In this post, we will explore how to use PyTorch to build powerful NLP models that can understand and generate human language.
Whether you are interested in sentiment analysis, machine translation, text generation, or any other NLP task, PyTorch provides the flexibility and performance needed to tackle these challenges. With its dynamic computation graph and easy-to-use APIs, PyTorch makes it easy to experiment with different architectures and algorithms for processing natural language data.
In this post, we will cover the following topics:
1. Introduction to Natural Language Processing and PyTorch
2. Preprocessing text data for NLP tasks
3. Building neural network models for NLP using PyTorch
4. Training and evaluating NLP models with PyTorch
5. Deploying and using NLP models in real-world applications
By the end of this post, you will have a solid understanding of how to leverage the power of PyTorch to build intelligent language applications that can understand, generate, and interact with human language. Stay tuned for more updates on NLP with PyTorch!
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