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Key benefits

Understand how to use PyTorch 1.x to build advanced neural network models

Learn to perform a wide range of tasks by implementing deep learning algorithms and techniques

Gain expertise in domains such as computer vision, NLP, Deep RL, Explainable AI, and much more

Description

Deep learning is driving the AI revolution, and 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 out of your data and build complex neural network models. The book starts with a quick overview of PyTorch and explores using convolutional neural network (CNN) architectures for image classification. You'll then work with recurrent neural network (RNN) architectures 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 and explore the world of generative adversarial networks (GANs). You'll not only build and train your own deep reinforcement learning models in PyTorch but also deploy PyTorch models to production using expert tips and techniques. Finally, you'll get to grips with training large models efficiently in a distributed manner, searching neural architectures effectively with AutoML, and rapidly prototyping models using PyTorch and fast.ai. 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 and music generating models using PyTorch

Build a deep Q-network (DQN) model in PyTorch

Export universal PyTorch models using Open Neural Network Exchange (ONNX)

Become well-versed with rapid prototyping using PyTorch with fast.ai

Perform neural architecture search effectively using AutoML

Easily interpret machine learning (ML) models written in PyTorch using Captum

Design ResNets, LSTMs, Transformers, and more using PyTorch

Find out how to use PyTorch for distributed training using the torch.distributed API

What do you get with Print?

Instant access to your digital copy whilst your Print order is Shipped

Paperback book shipped to your preferred address

Redeem a companion digital copy on all Print orders

Access this title in our online reader with advanced features

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Amazon verified reviews

Amazon Customer Feb 19, 2021

Great Book, A very detailed introduction on Pytorch. Well explained concepts. Fantastic book to be introduced into Machine learning and Pytorch

Amazon Verified review

Nivedita Jha Feb 15, 2021

Amazing book! A good read for beginners covered the basic details in very crisp and clear with good examples. The very good summary allows you to understand the key aspects of the discipline(s) without daunting complexity.I've found this book very comprehensive and it shows the efforts that have been put in by the writer.The content of this book deserves 5 stars. I especially appreciate the author for writing such a great book that will help us to understand and learn the basic concepts of PyTorch and mastering in it.In short , Great book, up to date, engaging and covers a lot of topics clearly.

shashank sagar jha Feb 22, 2021

Best book.. Superb clarity.. Best part is the examples provided in this book. Almost all important topics are covered in depth.

deepak Feb 23, 2021

I did not work with PyTorch before and although the book states the basic knowledge of PyTorch as a pre-requisite, I was still able to learn from scratch thanks to the easy progression of topics. The book does cover a lot of ground in my opinion ranging from model architectures, to applications such as music generation and to model deployment and other such engineering considerations. The second half of the book helps get a feel of how deep learning works in practice in real-world applications. I especially liked the inclusion of a jupyter notebook based exercise in each and every chapter. Definitely worth a read.

Shalini Jha Feb 15, 2021

This book is a holy grail for beginners, who wants to learn pytorch at home.I appreciate the author to cover each and every concept of pytorch in the most simplest yet crisp manner.The content is described from scratch capturing every details...very basic to implementable level.The book has lot of examples to cover and explain the concepts. I would blindly recommend this book to anyone who wants to learn pytorch at home.It keeps reader engrossed and involved, kudos to author for such a pleasant compression.

Mastering PyTorch: Build powerful neural network architectures using advanced PyTorch 1.x features

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