Lecture
This lecture covers the uni-dimensional and multi-dimensional Gaussian functions, including their pdf representations, mean, and variance. It also explains how to model data using a Gaussian function, decompose the covariance matrix, and derive optimal parameters. The likelihood function and maximum likelihood optimization are discussed, emphasizing the importance of finding the optimal mean and covariance of the data.