Published Paper Details:

The main motive of our image classifier is to classify images of skin cancer, such as basal cell carcinoma, squamous cell carcinoma, melanoma and so on, using Machine Learning algorithms and Convolutional Neural Network models. This model can recognize images based on previously trained images and co- relate the image to the closest form of skin cancer. Classification is a process of categorizing a given set of data into classes, It can be performed on both structured or unstructured data. Image classification is a widely used method for categorizing things, and one area where it's particularly popular is in identifying different types of skin cancer. Skin cancer is a very serious form of cancer that is causing more deaths as people don't always know the symptoms or how to prevent it. The severity of the cancer depends on the type of skin cancer. This research project uses a dataset called HAM10000, which contains over 10,000 images. When creating a model to classify these images, using data augmentation helps the model learn more distinctive characteristics and features than not using data augmentation.