Building YOLO Neural Networks for Object Detection in Python and PyTorch - Part 1

Learn to implement YOLO (You Only Look Once) neural networks from scratch in a 21-minute video tutorial focused on object detection using Python and PyTorch. Master the fundamentals of deep learning behind YOLO models, including proper image preprocessing through data augmentation and training Feature Pyramid Networks (FPN) for multi-scale object detection. Explore key concepts like YOLO-Darknet backbone architecture, network neck and head components, loss functions, and post-processing techniques including Non-Maximum Suppression (NMS). Code along to build a complete object detection system while understanding common implementation challenges and their solutions through Feature Pyramid Networks. Access supplementary code, documentation, and animations through the provided Patreon links to enhance the learning experience.