lot of labeled data naturally so unsupervised learning then is we have training data and it doesn't have labels so the goal here is to identify interesting structure in the data because we don't know the answer is necessarily but you can see in the graph they have associated here because I'm supervising something people don't grasp as easily because you're kind of thinking well what would be the point of this but one example is anomaly detection so that's when you're trying to something that's a complete outlier and