Mastering Computer Vision with Pytorch 2. 0 : Discover, Design, and Build Cutting-Edge High Performance Computer Vision Solutions with Pytorch 2. 0 and Deep Learning Techniques (English Edition).

Format:

Book

Author/Creator:

Siddiqui, M. Arshad.

Language:

English

Subjects (All):

Machine learning.

Artificial intelligence.

Physical Description:

1 online resource (206 pages)

Edition:

1st ed.

Place of Publication:

Delhi : Orange Education PVT Ltd, 2025.

Summary:

In an era where Computer Vision has rapidly transformed industries like healthcare and autonomous systems, PyTorch 2.0 has become the leading framework for high-performance AI solutions. [Mastering Computer Vision with PyTorch 2.0] bridges the gap between theory and application, guiding readers through PyTorch essentials while equipping them to solve real-world challenges. Starting with PyTorch's evolution and unique features, the book introduces foundational concepts like tensors, computational graphs, and neural networks. It progresses to advanced topics such as Convolutional Neural Networks (CNNs), transfer learning, and data augmentation. Hands-on chapters focus on building models, optimizing performance, and visualizing architectures. Specialized areas include efficient training with PyTorch Lightning, deploying models on edge devices, and making models production-ready. Explore cutting-edge applications, from object detection models like YOLO and Faster R-CNN to image classification architectures like ResNet and Inception. By the end, readers will be confident in implementing scalable AI solutions, staying ahead in this rapidly evolving field. Whether you're a student, AI enthusiast, or professional, this book empowers you to harness the power of PyTorch 2.0 for Computer Vision.

Contents:

Cover Page

Title Page

Copyright Page

Dedication Page

About the Author

About the Technical Reviewers

Acknowledgements

Preface

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Errata

Table of Contents

1. Diving into PyTorch 2.0

Introduction

Structure

Brief Overview of PyTorch

PyTorch and Computer Vision

Origin and Emergence of PyTorch

PyTorch’s Philosophy and Early Days

Evolution and Growth of PyTorch

Adoption of PyTorch

The Importance of Virtual Environments and Creating Them

For Ubuntu

For Mac

Installing PyTorch

Troubleshooting Tips

Setting Up the Development Environment on Jupyter Notebook

Dynamic Computation Graphs and the Define-by-Run Paradigm

The Autograd System

GPU Acceleration

Distributed Computing Generated by AI.

Notes:

Description based on publisher supplied metadata and other sources.

Part of the metadata in this record was created by AI, based on the text of the resource.

Other Format:

Print version: Siddiqui, M. Arshad Mastering Computer Vision with Pytorch 2. 0

ISBN:

9789348107084

OCLC:

1490380321