Deep Learning with PyTorch, Second Edition [Audiobook]

Everything you need to create neural networks with PyTorch, including Large Language and diffusion models.

PyTorch core developer Howard Huang updates the bestselling original Deep Learning with PyTorch with new insights into the transformers architecture and generative AI models.

In Deep Learning with PyTorch, Second Edition you’ll find

Deep learning fundamentals reinforced with hands-on projects
Mastering PyTorch's flexible APIs for neural network development
Implementing CNNs, transformers, and diffusion models
Optimizing models for training and deployment
Generative AI models to create images and text

Instantly familiar to anyone who knows PyData tools like NumPy, PyTorch simplifies deep learning without sacrificing advanced features. In Deep Learning with PyTorch, Second Edition you’ll learn how to create your own neural network and deep learning systems and take full advantage of PyTorch’s built-in tools for automatic differentiation, hardware acceleration, distributed training, and more. You’ll discover how easy PyTorch makes it to build your entire DL pipeline, including using the PyTorch Tensor API, loading data in Python, monitoring training, and visualizing results. Each new technique you learn is put into action with practical code examples in each chapter, culminating into you building your own convolution neural networks, transformers, and even a real-world medical image classifier.