These slides are from last year. During the quarter we may post updated versions here.

Introduction

Probability on finite sets

Random variables

Estimation and prediction

Random vectors

Classification

Continuous random variables

Continuous random vectors

Conditional density

MMSE estimation

The linear model

Recursive estimation

The Kalman filter

Gaussian stochastic processes

Estimating moments

Regression and learning

Bias and variance

Detection