The 9 Best PyTorch Books

PyTorch is a powerful open-source deep learning platform that provides a seamless path from research prototyping to production deployment. In this post, we will be looking at the 9 best PyTorch books.

1. Deep Learning with PyTorch by Eli Stevens, Luca Antiga, and Thomas Viehmann is a great book for those who are already familiar with deep learning and are looking to get started with PyTorch. The book covers all the basics of PyTorch including autograd, dataset loading and processing, building neural networks, and more.

2. Deep Learning for Coders with Fastai and PyTorch by Jeremy Howard and Sylvain Gugger is a great book for those who want to learn deep learning from scratch using PyTorch. The book covers all the basics of deep learning including linear algebra, calculus, and statistics. It also introduces readers to fastai—a high-level library built on top of PyTorch—which makes it easy to build complex models quickly.

3. Programming PyTorch for Deep Learning by Ian Pointer is a great book for developers who want to get started with deep learning using PyTorch. The book covers all the basics of PyTorch including Tensors, autograd,nn Module API, dataset loading and processing, CUDA integration, and more. It also includes several practical examples of how to use PyTorch in different domains such as computer vision and natural language processing.

4. Natural Language Processing with PyTorch by Delip Rao and Brian McMahan is a great book for those who want toapply deep learning to natural language processing (NLP). The book covers all the key NLP tasks including text classification, sequence labeling, machine translation, question answering, and more. It also introduces readers to popular NLP libraries such as spaCy and NLTK.

5. Pytorch Recipes by Pradeep Singh & Vishnu Subramanian is a great book for those who want to learn how to build popular deep-learning models using Pytorch. The book covers all the basics of deep learning including linear algebra, calculus, statistics, optimization methods, and more. It also includes several practical examples of how to use Pytorch in different domains such as computer vision and natural language processing.

6 . Pytorch Pocket Reference by Brian McMahon is a great book for those who want a quick reference guide for Pytorch. The book covers all the key concepts of Pytorch including Tensors, autograd, nn Module API, dataset loading, and more. It also includes several code snippets that demonstrate how to use Pytorch in different domains such as computer vision and natural language processing.

7 . Mastering Pytorch by Nathan Inkawhich is a great book for those who want to take their knowledgeofPytorchtothe next level. The book covers advanced topics such as data parallelism, distributed training, performance optimization, and more. It also includes several practical examples of howPytorchoften used in scientific research papers.

8 . Modern Computer Vision with Pytorch by Jochen Gast is a great book for those who want to get started with computer vision using Pytorch as their main deep learning framework. The book covers all the key concepts including image classification, object detection, semantic segmentation, and more. It also includes several code snippets that demonstrate the effective use of Pytorch in commercial applications such as Autonomous Vehicles and Face Recognition.

9 . Make Your First GAN With PyTorch edited by Hugo Laurensis a great book for those simply wanting to understand the theory behind generative adversarial networks(GAN) and their implementation PyTorch network(DCGAN) popularized in papers like “Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks”.

These are 9 of the best books currently available when it comes to learning about PyTorch or even just understanding certain complex models within the Deep Learning space (i.e GAN’s).

While incorporating PyTorch into your project may be daunting at first – going through any one of these books will give you the insights you need in order not just to get your project off the ground – but excel in your field!