Learning PyTorch 2.0
Minimum price
Suggested price

Learning PyTorch 2.0

Experiment deep learning from basics to complex models using every potential capability of Pythonic PyTorch

About the Book

This book is a comprehensive guide to understanding and utilizing PyTorch 2.0 for deep learning applications. It starts with an introduction to PyTorch, its various advantages over other deep learning frameworks, and its blend with CUDA for GPU acceleration. We delve into the heart of PyTorch – tensors, learning their different types, properties, and operations. Through step-by-step examples, the reader learns to perform basic arithmetic operations on tensors, manipulate them, and understand errors related to tensor shapes.

A substantial portion of the book is dedicated to illustrating how to build simple PyTorch models. This includes uploading and preparing datasets, defining the architecture, training, and predicting. It provides hands-on exercises with a real-world dataset. The book then dives into exploring PyTorch's nn module and gives a detailed comparison of different types of networks like Feedforward, RNN, GRU, CNN, and their combination.

Further, the book delves into understanding the training process and PyTorch's optim module. It explores the overview of optimization algorithms like Gradient Descent, SGD, Mini-batch Gradient Descent, Momentum, Adagrad, and Adam. A separate chapter focuses on advanced concepts in PyTorch 2.0, like model serialization, optimization, distributed training, and PyTorch Quantization API.

In the final chapters, the book discusses the differences between TensorFlow 2.0 and PyTorch 2.0 and the step-by-step process of migrating a TensorFlow model to PyTorch 2.0 using ONNX. It provides an overview of common issues encountered during this process and how to resolve them.

Key Learnings

  • A comprehensive introduction to PyTorch and CUDA for deep learning.
  • Detailed understanding and operations on PyTorch tensors.
  • Step-by-step guide to building simple PyTorch models.
  • Insight into PyTorch's nn module and comparison of various network types.
  • Overview of the training process and exploration of PyTorch's optim module.
  • Understanding advanced concepts in PyTorch like model serialization and optimization.
  • Knowledge of distributed training in PyTorch.
  • Practical guide to using PyTorch's Quantization API.
  • Differences between TensorFlow 2.0 and PyTorch 2.0.
  • Guidance on migrating TensorFlow models to PyTorch using ONNX.

Table of Content

  1. Introduction to Pytorch 2.0 and CUDA 11.8
  2. Getting Started with Tensors
  3. Advanced Tensors Operations
  4. Building Neural Networks with PyTorch 2.0
  5. Training Neural Networks in PyTorch 2.0
  6. PyTorch 2.0 Advanced
  7. Migrating from TensorFlow to PyTorch 2.0
  8. End-to-End PyTorch Regression Model


A perfect and skillful book for every machine learning engineer, data scientist, AI engineer and data researcher who are passionately looking towards drawing actionable intelligence using PyTorch 2.0. Knowing Python and the basics of deep learning is all you need to sail through this book.

  • Share this book

  • Categories

    • Artificial Intelligence
    • Python
    • Distributed Systems
  • Feedback

    Email the Author(s)

About the Editor

GitforGits | Asian Publishing House
GitforGits | Asian Publishing House

GitforGits is an Asian publishing house where knowledgeable experts and open-source contributors collaborate to disseminate new ideas and innovations. We plan to provide niche, original, and useful content; we are a self-funded, independent publisher. We have books spanning the fields of computer science, cybersecurity, cloud computing, devops, deep learning, hardware programming, networking, the Internet of Things, and any other area of technology to which we can satisfactorily contribute.

The Leanpub 60-day 100% Happiness Guarantee

Within 60 days of purchase you can get a 100% refund on any Leanpub purchase, in two clicks.

See full terms

80% Royalties. Earn $16 on a $20 book.

We pay 80% royalties. That's not a typo: you earn $16 on a $20 sale. If we sell 5000 non-refunded copies of your book or course for $20, you'll earn $80,000.

(Yes, some authors have already earned much more than that on Leanpub.)

In fact, authors have earnedover $12 millionwriting, publishing and selling on Leanpub.

Learn more about writing on Leanpub

Free Updates. DRM Free.

If you buy a Leanpub book, you get free updates for as long as the author updates the book! Many authors use Leanpub to publish their books in-progress, while they are writing them. All readers get free updates, regardless of when they bought the book or how much they paid (including free).

Most Leanpub books are available in PDF (for computers) and EPUB (for phones, tablets and Kindle). The formats that a book includes are shown at the top right corner of this page.

Finally, Leanpub books don't have any DRM copy-protection nonsense, so you can easily read them on any supported device.

Learn more about Leanpub's ebook formats and where to read them

Write and Publish on Leanpub

You can use Leanpub to easily write, publish and sell in-progress and completed ebooks and online courses!

Leanpub is a powerful platform for serious authors, combining a simple, elegant writing and publishing workflow with a store focused on selling in-progress ebooks.

Leanpub is a magical typewriter for authors: just write in plain text, and to publish your ebook, just click a button. (Or, if you are producing your ebook your own way, you can even upload your own PDF and/or EPUB files and then publish with one click!) It really is that easy.

Learn more about writing on Leanpub