Let’s be frank. Machine learning is not about algorithms. Number one question in machine learning is data: how to collect and process it. Number two question is labeling. Machine learning engineers love labels and hate labeling. We spend time and resources, we invite humans in the game to say explicitly what the right answer is. But sometimes we want to be cautious and avoid trusting judgments. This helps us to perceive what the data actually mean, and to find hidden rules. Today we’ll look at a few business cases and figure out how to apply unsupervised machine learning in order to create powerful systems.