Mastering PyTorch: Create and deploy deep learning models from CNNs to multimodal models, LLMs, and beyond, Edition 2

• Understand how to use PyTorch to build advanced neural network models
• Get the best from PyTorch by working with Hugging Face, fastai, PyTorch Lightning, PyTorch Geometric, Flask, and Docker
• Unlock faster training with multiple GPUs and optimize model deployment using efficient inference frameworks

• Implement text, vision, and music generation models using PyTorch
• Build a deep Q-network (DQN) model in PyTorch
• Deploy PyTorch models on mobile devices (Android and iOS)
• Become well versed in rapid prototyping using PyTorch with fastai
• Perform neural architecture search effectively using AutoML
• Easily interpret machine learning models using Captum
• Design ResNets, LSTMs, and graph neural networks (GNNs)
• Create language and vision transformer models using Hugging Face

This deep learning with PyTorch book is for data scientists, machine learning engineers, machine learning researchers, and deep learning practitioners looking to implement advanced deep learning models using PyTorch. This book is ideal for those looking to switch from TensorFlow to PyTorch. Working knowledge of deep learning with Python is required.