Book Image

Mastering PyTorch - Second Edition

By : Ashish Ranjan Jha
4 (1)
Book Image

Mastering PyTorch - Second Edition

4 (1)
By: Ashish Ranjan Jha

Overview of this book

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.
Table of Contents (21 chapters)
20
Index

Index

A

Accelerate 277, 499, 508

using, to speed up PyTorch model training 508-510

actions 300

action-value function 304

activation functions 10, 21

leaky ReLU 12, 13

rectified linear units (ReLUs) 11, 12

sigmoid 10, 11

TanH 11

actor-critic method 303

Adadelta 14, 15

Adagrad 14

Adam optimizer 15, 16, 38, 105

agent 300

agent, training in Model-Free RL setting

policy optimization 303, 304

Q-learning 304

AlexNet 44, 55

fine-tuning 55-58

fine-tuning, with PyTorch 58-65

AlphaZero 303

Amazon Machine Image (AMI) 381

Amazon SageMaker

TorchServe, using with 383

Amazon Web Services (AWS) 347, 381, 508

PyTorch, using with 381

Android

PyTorch model, deploying on 392

Android app

development environment, setting up 393-395

phone camera, using to capture images 395, 396

Android mobile device

app, launching 405-409

Android NDK (Native Development Kit) 393

Android...