Skin cancer is the most common human malignancy, is primarily diagnosed visually, beginning with an initial clinical screening and followed potentially by dermoscopic analysis, a biopsy and histopathological examination. Automated classification of skin lesions using images is a challenging task owing to the fine-grained variability in the appearance of skin lesions.the HAM10000 ("Human Against Machine with 10000 training images") dataset.It consists of 10015 dermatoscopicimages which are released as a training set for academic machine learning purposes and are publiclyavailable through the ISIC archive. This benchmark dataset can be used for machine learning and for comparisons with human experts.
Demo Application Deployed on Heruko
Notebook code for this application Available here
