A Criminally Short Introduction to Semi-Supervised Learning

Because there are more interesting problems than there are labeled datasets, semi-supervised learning provides a framework for getting feedback from the environment as a proxy for labels of what's "correct."  Of all the machine learning methodologies, it might also be the closest to how humans usually learn--we go through the world, getting (noisy) feedback on the choices we make and learn from the outcomes of our actions.  

Link: David Silver's Reinforcement Learning course