Explores probabilistic linear regression, covering joint and conditional probability, ridge regression, and overfitting mitigation.
Explores Variational Auto-Encoders, Bayesian inference, attention-based latent spaces, and the effectiveness of Transformers in language processing.
Explores maximum likelihood inference, comparing models based on likelihood ratios and demonstrating with a coin example.
Covers the Stochastic Block Model and its application in community detection, exploring its mathematical formulation and challenges.
