Skin Cancer Detection app
This is a project on skin cancer detection web app which has been implemented with flask framework and deployed on Heroku. The model has been built using fastai deep learning library which is a high level api for pytorch. The classifier has been trained using skin dataset collected from google and loaded to Kaggle which contains 400 images of three categories of pigmented skin lesions. The classifier has been built with transfer learning technique using a pretrained Densenet169 model. The final classifer achieved an accuracy of 91.2% and a F1-score of 91.7% on validation data.
