This lecture summary discusses the foundations on which PAC Learning, a machine learning model, is based on. This model focuses on inductively learning an unknown target function, given only training examples of this target function and a space of candidate hypotheses. The questions that we will concern are how many training examples are sufficient to successfully learn the target function, and...
