Probability Tutorial

Explore the fundamental concepts of probability in this 43-minute tutorial from the MIT BMM Summer Course 2018, presented by Andrei Barbu. Dive into topics such as uncertainty, maximizing rewards, means and variances, Bayesian reasoning, and probability distributions including Gaussians and Poisson. Examine graphical models, hidden Markov models, and Markov chains, while learning about their applications in areas like formant analysis. Gain a comprehensive understanding of probability theory and its practical implications through experiments and real-world examples.

Intro
Uncertainty
Maximizing Rewards
Why Probability
Means and Variances
Improbability
Bayesian Reasoning
Experiments
Probability distributions
gaussians
multivariate Gaussians
Poisson distributions
Bayesian update
Graphical models
Formants
Graphical Model
Hidden Markov Model
Markov Chain
Summary