Alzheimer-Classification

The goal of this project is to develop a robust image classification model to distinguish between different neurological conditions. The notebook demonstrates the process from data loading and preprocessing to model training, evaluation, and visualization of results.

The dataset consists of image files categorized into three classes: AD, CONTROL, and PD. The notebook includes code to count the number of images in the training and testing folders for each class.

Train folder:

AD: 2561 images

CONTROL: 3010 images

PD: 906 images

Test folder:

AD: 639 images

CONTROL: 662 images

PD: 61 images