Kernel Methods
Solve non-linear problems. Similarity measures between two data points. Moves point to different spaces in different dimensions. eg. Support Vector Machine, K-means Clustering. Work in feature space, not in data space. Encode data into feature space. Convert non-linearity to linear model. Good Resources: https://www.youtube.com/watch?v=uDAAi5aQbMU