Computer vision based melanoma diagnosis has been a side project of mine on and off for almost 2 years now, so I plan on making this the first of a short series of posts on the topic. This post is intended as a quick/informative read for those with basic machine learning experience looking for an introduction to the ISIC problem, and those just getting out of their first or second machine learning/data mining course who'd like a simple problem to get their hands dirty with. Tools for early diagnosis of different diseases are a major reason machine learning has a lot of people excited today. The process for these innovations is a long one: Labeled datasets need built, engineers and data scientists need trained, and each problem comes with its own set of edge cases that often make building robust classifiers very tricky (even for the experts). Here I'm going to focus on building a classifier.