Clustering with Scikit with GIFs

It's a common task for a data scientist: you need to generate segments (or clusters- I'll use the terms interchangably) of the customer base. With definitions, of course!!! Clustering is the subfield of unsupervised learning that aims to partition unlabelled datasets into consistent groups based on some shared unknown characteristics. All the tools you'll need are in Scikit-Learn, so I'll leave the code to a minimum. Instead, through the medium of GIFs, this tutorial will describe the most common techniques. If GIFs aren't your thing (what are you doing on the internet?), You can download this jupyter notebook here and the gifs can be downloaded from this folder (or you can just right click on the GIFs and select'Save image as…'). Clustering algorithms can be broadly split into two types, depending on whether the number of segments is explicitly specified by the user.