Modern Computer Vision with PyTorch
Starting from the basics of neural networks, this book covers over 50 applications of computer vision and helps you to gain a solid understanding of the theory of various architectures before implementing them. Each use case is accompanied by a notebook in GitHub with ready-to-execute code and self-assessment questions.
Offered by
Difficulty Level
Intermediate
Completion Time
27h28m
Language
English
About Book
Who Is This Book For?
This book is for beginners to PyTorch and intermediate-level machine learning practitioners who are looking to get well-versed with computer vision techniques using deep learning and PyTorch. If you are just getting started with neural networks, you’ll find the use cases accompanied by notebooks in GitHub present in this book useful. Basic knowledge of the Python programming language and machine learning is all you need to get started with this book.
Modern Computer Vision with PyTorch
- About Book
- Who Is This Book For?
- Book Content
Book content
chapters • 27h28m total length
Artificial Neural Network Fundamentals
PyTorch Fundamentals
Building a Deep Neural Network with PyTorch
Introducing Convolutional Neural Networks
Transfer Learning for object Classification
Practical Aspects of Image Classification
Basics of Object detection
Advanced object detection
Image segmentation
Applications of object detection and localization
Autoencoders and Image Manipulation
Image generation using GAN
Advanced GANs to manipulate images
Training with minimal data points
Combining Computer Vision and NLP techniques
Combining Computer Vision and Reinforcement Learning
Moving a Model to Production
OpenCV utilities for image analysis
Related Resources
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