...The repository contains hundreds of Jupyter notebooks that are richly annotated and organized by topic, progressing from basic Python and PyTorch fundamentals to advanced neural network designs like ResNet, transformers, and object detection algorithms. Itβs not just a dry code repository; it includes theoretical explanations alongside hands-on examples, loss function explorations, optimization routines, and full end-to-end experiments on real datasets, making it highly suitable for both self-study and classroom use.