Skin Lesion Classification Malignant vs Benign using ISIC skin Cancer data and MobileNet (university Graduation Project)

I solved class imbalance problem using Data augmentation

I used Transfer learning model such as MobileNet Model with freezing and unfreezing technique

I used different callbacks during compile and fit process like early stopping and ReduceLRonPlateau

I used different classification metrics like precision , recall ,confusion matrix, loss and Accuracy

I achieved 96.40% test accuracy , 93.26% test precision , and 100% test recall

Tools used (Numpy,Pandas,Keras,Tensorflow,Sklearn)