Our supervised machine learning project was a success and we're well on our way to becoming experts in recommender systems. It's now time to leave behind the safety of our neatly tagged data and venture into the unknown. Yes, I'm talking about unsupervised machine learning. In this chapter, we'll train a model that will help us find hidden patterns in a mountain of data. And since we've come so far on our journey of learning Julia, it's time to take off the training wheels and take on our first client.
Just kidding—for now, we'll play pretend, but we'll indeed tackle a machine learning problem that could very well be one of the first tasks of a junior data scientist. We'll help our imaginary customer discover key insights for supporting their advertising strategy, a very important component...
