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Mastering PyTorch - - Build powerful deep learning architectures using advanced PyTorch features (Paperback, 2nd Revised edition)
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Mastering PyTorch - - Build powerful deep learning architectures using advanced PyTorch features (Paperback, 2nd Revised edition)
Expected to ship within 10 - 15 working days
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Master advanced techniques and algorithms for machine learning with
PyTorch using real-world examples Key Features * Understand how to
use PyTorch to build advanced neural network models including graph
neural networks and reinforcement learning models * Learn the
latest tech, such as generating images from text using diffusion
models * Become an expert in deploying PyTorch models in the cloud,
on mobile and across platforms * Get the best from PyTorch by
working with key libraries, including Hugging Face, fast.ai, and
PyTorch Lightning Book Description PyTorch is making it easier than
ever before for anyone to build deep learning applications. This
PyTorch book will help you uncover expert techniques to get the
most from your data and build complex neural network models. You'll
create convolutional neural networks (CNNs) for image
classification and recurrent neural networks (RNNs) 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. You'll not only build and
train your own deep reinforcement learning models in PyTorch but
also deploy PyTorch models to production, including mobiles and
embedded 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
fast.ai for prototyping models to training models using PyTorch
Lightning. You'll discover libraries for AutoML and explainable AI,
create recommendation systems using TorchRec, and build language
and vision transformers with Hugging Face. By the end of this
PyTorch book, you'll be able to perform complex deep learning tasks
using PyTorch to build smart artificial intelligence models. What
you will learn * Implement text, image, and music generating models
using PyTorch * Build a deep Q-network (DQN) model in PyTorch *
Deploy PyTorch models on mobiles and embedded devices * Become
well-versed with rapid prototyping using PyTorch with fast.ai *
Perform neural architecture search effectively using AutoML *
Easily interpret machine learning models using Captum * Develop
your own recommendation system using TorchRec * Design ResNets,
LSTMs, and graph neural networks * Create language and vision
transformer models using Hugging Face Who This Book Is For This
book is for data scientists, machine learning researchers, and deep
learning practitioners looking to implement advanced deep learning
models using PyTorch. This book is an ideal resource for those
looking to switch from TensorFlow to PyTorch. Working knowledge of
deep learning with Python programming is required.
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