Mastering PyTorch. Create and deploy deep learning models from CNNs to multimodal models, LLMs, and beyond - Second Edition - Onepress
Tytuł oryginału: Mastering PyTorch. Create and deploy deep learning models from CNNs to multimodal models, LLMs, and beyond - Second Edition
ISBN: 9781801079969
stron: 558, Format: ebook
Data wydania: 2024-05-31
Księgarnia: Onepress
Cena książki: 134,10 zł (poprzednio: 149,00 zł)
Oszczędzasz: 10% (-14,90 zł)
PyTorch is making it easier than ever before for anyone to build deep learning applications. This PyTorch deep learning book will help you uncover expert techniques to get the most out of your data and build complex neural network models.
You’ll build convolutional neural networks for image classification and recurrent neural networks and transformers for sentiment analysis. As you advance, you'll apply deep learning across different domains, such as music, text, and image generation, using generative models, including diffusion models. You'll not only build and train your own deep reinforcement learning models in PyTorch but also learn to optimize model training using multiple CPUs, GPUs, and mixed-precision training. You’ll deploy PyTorch models to production, including mobile devices. Finally, you’ll discover the PyTorch ecosystem and its rich set of libraries. These libraries will add another set of tools to your deep learning toolbelt, teaching you how to use fastai to prototype models and PyTorch Lightning to train models. You’ll discover libraries for AutoML and explainable AI (XAI), create recommendation systems, and build language and vision transformers with Hugging Face.
By the end of this book, you'll be able to perform complex deep learning tasks using PyTorch to build smart artificial intelligence models.
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Spis treści
Mastering PyTorch. Create and deploy deep learning models from CNNs to multimodal models, LLMs, and beyond - Second Edition eBook -- spis treści
- 1. Overview of Deep Learning using PyTorch
- 2. Deep CNN architectures
- 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 TorchRec
- 19. PyTorch and Hugging Face