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Mastering PyTorch

You're reading from   Mastering PyTorch Create and deploy deep learning models from CNNs to multimodal models, LLMs, and beyond

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Product type Paperback
Published in May 2024
Publisher Packt
ISBN-13 9781801074308
Length 558 pages
Edition 2nd Edition
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Author (1):
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Ashish Ranjan Jha Ashish Ranjan Jha
Author Profile Icon Ashish Ranjan Jha
Ashish Ranjan Jha
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Table of Contents (21) Chapters Close

Preface 1. Overview of Deep Learning Using PyTorch 2. Deep CNN Architectures FREE CHAPTER 3. Combining CNNs and LSTMs 4. Deep Recurrent Model Architectures 5. Advanced Hybrid Models 6. Graph Neural Networks 7. Music and Text Generation with PyTorch 8. Neural Style Transfer 9. Deep Convolutional GANs 10. Image Generation Using Diffusion 11. Deep Reinforcement Learning 12. Model Training Optimizations 13. Operationalizing PyTorch Models into Production 14. PyTorch on Mobile Devices 15. Rapid Prototyping with PyTorch 16. PyTorch and AutoML 17. PyTorch and Explainable AI 18. Recommendation Systems with PyTorch 19. PyTorch and Hugging Face 20. Index

Mastering Pytorch, Second Edition: Build powerful deep learning architectures using advanced PyTorch features

Welcome to Packt Early Access. We’re giving you an exclusive preview of this book before it goes on sale. It can take many months to write a book, but our authors have cutting-edge information to share with you today. Early Access gives you an insight into the latest developments by making chapter drafts available. The chapters may be a little rough around the edges right now, but our authors will update them over time.

You can dip in and out of this book or follow along from start to finish; Early Access is designed to be flexible. We hope you enjoy getting to know more about the process of writing a Packt book.

  1. Chapter 1: Overview of Deep Learning with PyTorch
  2. Chapter 2: Combining CNNs and LSTMs
  3. Chapter 3: Deep CNN architectures
  4. Chapter 4: Deep Recurrent Model Architectures
  5. Chapter 5: Hybrid Advanced Neural Networks
  6. Chapter 6: Graph Neural...
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