Deep Learning for Computer Vision from Scratch

I know the hype is all around LLMs right now, but deep learning for computer vision continues to drive advancements in AI too – from your smartphone to applications at airports. Perhaps you would like to learn how to build yours.

This past summer, I had the privilege of teaching a 3-day course on Deep Learning for Computer Vision.

The course materials are now open source and available on GitHub: https:github.com/exponentialR/DL4CV

In the course, we began with a recap of Python and an introduction to PyTorch, then explored image computation techniques. We progressed from coding a simple neural network from the ground up to building basic architectures and advancing to deep neural networks such as VGG, ResNet, and YOLO. We also performed inference for emotion recognition, traffic tracking, and simple object tracking.

The repository contains:

• Lecture slides

• Practical code samples (in PyTorch)

• Datasets for hands-on projects

• Step-by-step notebook tutorials

Feel free to explore, fork, and contribute. Your feedback is always welcome. #DeepLearning #ComputerVision #OpenSource