This lecture covers the statistical justification of the Least Squares method, explaining the error terms, independently and identically distributed random variables, likelihood function, logistic regression, Perceptron learning algorithm, and Generalized Linear Models. The instructor discusses the exponential family, natural parameters, and canonical parameters, emphasizing the relationship between data and parameters.