Skin Cancer Classification Application Using Machine Learning

Melanoma is one of the predominant types of skin cancer. The affected number has been increasing year after year. Although the deaths can be minimized by early detection and there is where the problem exists and consulting a dermatologist may not always guarantee the success of early detection and diagnoses. At first, the dermatologist examines the skin visually and decides whether it’s a type of skin cancer or a skin allergy. The accuracy of the diagnosis directly corresponds to the experience of the dermatologist. Even a small error in the inspection of the skin might end a life of a person so it is really necessary to have a standard and supporting system which can help dermatologists to identify and diagnose the patients is necessary. So with the advancements in image processing and deep learning algorithms have unleashed the potential to classify and identify the type of skin cancer with a single click of an image. The traditional method involves a lot of pre-processing steps and if something goes wrong in that step the model doesn’t perform well. The accuracy won’t be up to the mark this is where the Convolutional Neural Networks come into the picture. These models don’t requ