In this notebook:
- Used PyTorch, PyTorch-Lightning, and Fastai to solve image classification tasks using both FCNN and CNN on the MNIST dataset.
- Prepare a custom dataset for the image classification task (cats and dog classifier).
- Used transfer learning to fine-tune a pre-trained model (ResNet50) on the custom dataset.
- Used Grad-CAM to visualize how the model predicts.
