Calendar of Topics (Tentative)
University Schedule
important dates of this course

To be updated

All assignments (homework) can be downloaded at Assignments section Calendar of Topics (Tentative)

Week 1Introduction 8/24/2017
 Formulation of Pattern Recognition problem
Week 2Intro. to Supervised Learning
 Bayesian Decision Theory
Week 3Naive Bayesian Classifier
 Parametric Methods Maximum Likelihood Estimation
 Bayesian Parameter Estimation
 Assignment 1 (Due 9/10, 2017)
Week 4Semi-parametric Classifier
 EM algorithm
Week 5Hidden Markov Model
 Hidden Markov Model
 Assignment 2 (Due 9/24, 2017)
Week 6Linear Discriminant Analysis
 Linear Discrimination)
 Final Project Proposal (Due 10/1, 2017)
Week 7ANN:Multilayer Perceptron 1
 ANN:Multilayer Perceptron 2
 Assignment 3 (Due 10/8, 2017)
Week 8Deep Learning Theory
 Deep Learning (Keras)
Week 9GAN-Generative Adversarial Network
 Fall Break (No class)
Week 10Midterm Exam (10/24/2017)
 Nonparametric model
 Assignment 4 (Due 10/29/2017)
Week 11Kernel Machines (SVM) 2 (Ch13)
 Kernel Machines (SVM) 1 (Ch13)
Week 12Genetic Algorithms
 Decision Tree (Ch9)
 Assignment 5 (Due 11/12/2017)
Week 13Unsupervised Learning
 Clustering (Ch7)
Week 14Graphical Models 1
 Graphical Models 2
Week 15Dimension Reduction
 Project Presentation 12/07/2017
Week 16Final Project
 Final Project Due 12/14/2017