To understand DL model architecture, training and testing process for image segmentation: https://github.com/mobarakol/tutorial_notebooks/blob/main/UNet_Model_BraTS.ipynb
To understand Training and testing for DL image classification using network architecture from lib: https://github.com/mobarakol/tutorial_notebooks/blob/main/CIFAR_10H_CNN.ipynb
To understand DL datalaoder, how to build dataloader from scratch with images in folders for multi-class classification: https://github.com/mobarakol/tutorial_notebooks/blob/main/tiny_imagenet.ipynb
To understand multi-label classification metrics: https://github.com/mobarakol/tutorial_notebooks/blob/main/Multi_Label_Instance_Classification.ipynb
To understand Vision Transformer from scratch: https://github.com/mobarakol/tutorial_notebooks/blob/main/ViT_Module_Visualization.ipynb
To understand explainability in CNN and Transformer: https://github.com/mobarakol/tutorial_notebooks/blob/main/GradCAM_CNN_Vs_ViT.ipynb