Skin lesions are various abnormalities on the skin that appear on a patient due to many different reasons. These can be due to the exposure of skin to harmful UV rays or they can be mere birthmarks or an uncontrolled growth in the skin tissue, defined as cancer. Not all skin lesions are cancerous and therefore it is important to identify them at an early stage which can potentially improve the survival rate in case the pigment on skin turns out to be cancerous. The proposed system helps the user to identify if the spots on the skin are cancerous or benign by using CNN. The model was trained on HAM10000 ("Human Against Machine with 10000 training images") dataset using convolutional neural network. The dataset comprised of seven different classes of skin lesions and augmentation was used to increase the number of images in the dataset.

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