This document discusses different methods of machine learning, including supervised learning where inputs are associated with expected outputs, unsupervised learning where outputs are not presented, reinforced learning where a teacher only indicates correctness, Hebbian learning based on weight adjustment through correlation, and gradient descent learning which minimizes error through weight updates based on the error gradient. These various learning methods are some of the most popular forms of learning in neural networks.