Probability can be very counter-intuitive. If you flip a coin, the probability of it turning up heads is 50%. But once joint probability or conditional probability (Bayesian) gets into the mix, our ...

Unlike older approaches to machine reasoning, in which each causal connection (“rain makes grass wet”) had to be explicitly taught, programs based on probabilistic approaches like Bayesian ...

The course will introduce the basic principles and algorithms used in Bayesian machine learning. This will include the Bayesian approach to regression and classification tasks, introduction to the ...

A 250-year-old mathematical theory could be used to create ‘self-aware’ machine learning systems that understand when they are out of their depth, according to a panel of senior quants. Bayes’ theorem ...

The Poisson distribution is widely used in artificial intelligence (AI) and machine learning. In Bayesian inference, probability distributions often help solve problems that would otherwise be ...

Basic knowledge in probability and first course in statistics such as ST202 or equivalent Probability Distribution Theory and Inference; ... Bayesian networks, Conditional independence, Markov random ...