Explores Bayesian techniques for extreme value problems, including Markov Chain Monte Carlo and Bayesian inference, emphasizing the importance of prior information and the use of graphs.
Introduces machine learning basics, covering data segmentation, clustering, classification, and practical applications like image classification and face similarity.
