Focuses on classifying eye diseases into four categories: normal, cataract, diabetic retinopathy, and glaucoma. Using a dataset of over 4,000 images, the model achieved an accuracy of 92%. The project involved data augmentation and fine-tuning techniques to improve model performance and ensure robustness.