Pattern Recognition, Fall 2026

Course Schedule

1st week

        09/08   Course overview, Chapter 1 : Introduction

2nd week

        09/15   Chapter 2 : Bayesian Decision Theory

3rd week

        09/22   Chapter 2 : Bayesian Decision Theory

4th week

        09/29   Chapter 2 : Bayesian Decision Theory

5th week

        10/06   Chapter 2 : Bayesian Decision Theory

6th week

        10/13   Chapter 2 : Bayesian Decision Theory

7th week

        10/20   Chapter 3 : Maximum-Likelihood and Bayesian Parameter Estimation

8th week

        10/27   Chapter 3 : Maximum-Likelihood and Bayesian Parameter Estimation

9th week

        11/03   Chapter 3 : Maximum-Likelihood and Bayesian Parameter Estimation

10th week

        11/10   Chapter 3 : Maximum-Likelihood and Bayesian Parameter Estimation

11th week

        11/17   Chapter 3 : Maximum-Likelihood and Bayesian Parameter Estimation

12th week

        11/24   Chapter 6 : Multilayer Neural Networks

13th week

        12/01   Chapter 6 : Multilayer Neural Networks

14th week

        12/08   Chapter 6 : Multilayer Neural Networks

15th week

        12/15   Term Project Demonstration & Presentation