Description
Deep Learning with PyTorch, Second Edition is a textbook on building, training, and deploying deep learning models using the PyTorch framework, published by Manning Online Academy. It is a practical, in-depth guide to building, training, and deploying deep learning models using the PyTorch framework. The book takes learners from basic deep learning concepts to advanced model development, with a focus on practical implementations with real-world datasets. The book covers neural network principles, optimization techniques, and modern architectures, while emphasizing PyTorch’s dynamic computational graph and production-ready workflows for research and industrial applications.
Deep Learning with PyTorch, Second Edition updates the best-selling original guide with new insights into transformer architectures and generative AI models. PyTorch, familiar to anyone familiar with PyData tools like NumPy and scikit-learn, simplifies deep learning without sacrificing advanced features. PyTorch makes it easy to build the powerful neural networks that underpin many of the modern advances in artificial intelligence. This second edition has been completely revised by PyTorch’s original developer, Howard Huang, to cover the latest features and applications, including generative AI models.
What you will learn in Deep Learning with PyTorch, Second Edition:
- Deep Learning Fundamentals Reinforced with Practical Projects
- Master the Flexible PyTorch APIs for Neural Network Development
- Implement CNNs, RNNs, and Transformers
- Optimize Models for Training and Deployment
- Generative AI Models for Creating Images and Text
- And…
book specifications
Publisher: Manning
Instructors: Luca Antiga, Eli Stevens, Howard Huang and Thomas Viehmann
Language: English
Number of pages: 668
Format: PDF, EPUB
book topics
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Downloadly link
File password (s): www.downloadly.ir
Size
38 MB
