Overview of Unsupervised Machine Learning Tasks & Applications

Although most of the applications of Machine Learning in our world are based on supervised machine learning algorithms and that's why this is where most of the investment goes into this direction. However, the majority of the available data is actually unlabeled: we have the input feature X, but we do not have the labels y. From here comes the importance of unsupervised learning. There are a lot of applications for unsupervised learning for example if you want to create a system that will take a few pictures of each item on a manufacturing production line and detect which items are defective. You can fairly easily create a system that will take pictures automatically, and this might give you thousands of pictures every day.