#6 Machine Learning Specialization [Course 1, Week 1, Lesson 2]

after supervised learning the most widely used form of machine learning is unsupervised learning let's take a look at what that means we've talked about civilized learning and this video is about unsupervised learning but don't let the name unsupervised through you unsupervised learning is I think just as super as supervised learning when we're looking at supervised learning in the last video record it looks something like this in the case of a classification problem each example was associated with an upward label y such as benign or malignant designated by the O's and Crosses in unsupervised learning we're given data that isn't associated with any output labels y say you're given data on patients and their tumor size and the patient's age but not whether the tumor was benign or malignant so the data set looked like this on the we're not asked to diagnose whether the tumor is benign or malignant because we're not given any labels y instead our job is to find some structure or some pattern or just find something interesting in the data this is unsupervised learning we call it unsupervised because we're not trying to supervise the algorithm to give some quote right answer for every input instead we ask the algorithm to figure out all by itself what's interesting or what patterns or structures they might be in this data with this particular data set an unsupervised learning algorithm might decide that the data can be assigned to two different groups or two different clusters and so you might decide that there's one cluster or group over here and there's another cluster or group over here this is a particular type of unsupervised learning called a clustering algorithm because it places the unlabeled data into different clusters and this turns out to be used oh maybe it's genetic for DNA microarrays the idea is to measure how much certain genes are expressed