Modern Computer Vision with PyTorch - Second Edition

Modern Computer Vision with PyTorch is your hands-on guide to mastering computer vision techniques using PyTorch 2.x. From understanding neural networks to implementing real-world solutions with cutting-edge models like CLIP and Stable Diffusion, this book offers practical approaches to solve a variety of computer vision problems such as object detection, segmentation, and automated image generation.

What this Book will help me do

• Master neural network basics and build deep learning models using PyTorch, enhancing your coding and deep learning workflow.
• Efficiently solve real-world problems including facial recognition, object detection, and human pose estimation through practical examples.
• Leverage advanced architectures like transformers and diffusion models for novel generative AI applications.
• Integrate computer vision with NLP and reinforcement learning for comprehensive AI applications.
• Gain confidence in deploying machine learning models to production environments with real-world deployment tactics.

Author(s)

V Kishore Ayyadevara and Yeshwanth Reddy bring years of experience in deep learning and computer vision to this book. Kishore has an extensive academic and industry background in AI and big data solutions, and Yeshwanth is a practiced machine learning engineer specializing in model development and production deployment. Together, they offer a balanced approach to teaching computer vision with pragmatic and clear explanations.

Who is it for?

This book is ideal for beginners in PyTorch or those with basic experience in Python programming seeking to enter the field of computer vision. It also caters to intermediate data scientists and machine learning practitioners looking to enhance their skills in deep learning and computer vision. If you aim to implement real-world CV solutions or wish to advance your understanding of state-of-the-art models, this book is for you.