Unsupervised Learning in Anaconda

Before discussing unsupervised learning, it might be a good idea to introduce supervised learning since most of us will be familiar with functions discussed in the previous chapters. For a function of y=f(x), usually we have values for independent variables of x₁, x₂, ... x_n and a set of corresponding values for a dependent variable of y. In previous chapters, we have discussed various types of functions, such as the single-factor linear model. Our task is to figure out the format of the function, given a set of input values. For supervised learning, we have two datasets: the training data and test data. For the training dataset, it has a set of input variables and related output values (also called a supervisory signal). A supervised learning algorithm analyzes the training data and produces an inferred function. Then, we apply this inferred...