CS567 Machine Learning : Spring 2002 (Class Schedule & Assignments)

Class Schedule, Lecture Notes and Assignments (Spring 2003)

Note: The course content is continuously modified based on the needs & interests of the class.
Please keep checking this page for updated course material for the week !

Date	Topics Covered	Lecture Notes	Handouts & Homeworks
Jan 14	Introduction to ML, Linear Algebra & Useful mathematical tools	Lecture I	Linear Algebra, Matlab Primer
Jan 21	Fundamental Issues in Learning Theory I: Optimization & Cost Functions, Complexity, Generalization	Lecture II	Bias-Variance Handout
Jan 28	Fundamental Issues in Learning Theory II: Inverse Problem, Functional Analysis & Kernel Representation	Lecture III	Reference Paper, Wiener Derivation
Feb 04	Catch Up !! Project Guidelines !!
Feb 11	Bayesian Learning : Bayesian Inference, Maximum Likelihood and EM algorithm, Density Estimation	Lecture VII	GaussMixEM
Feb 18	Supervised Learning I : Linear Regression Methods, Least Squares, BLUE Estimate, Shrinkage and subset selection.	Lecture IV	HW1, housing[data,names]
Feb 25	Supervised Learning II : Linear Classification methods- LDA, QDA, Logistic Regression, Separating Hyperplanes	Lecture V	BayesDecTheory
Mar 04	Supervised Learning III : Support Vector Machines, Support Vector Regression, Large Margin Methods	Lecture VI	Tutorial [class, regress], SVMseq
Mar 11	Mid Term Examination (30% Grades)	(5-6pm) Closed Book
Mar 18	*Spring Break - No Class*
Mar 25	Supervised Learning IV: Nonparametric methods, RBFs, Locally Weighted Learning, Kernel Methods	Lecture VIII	LWL paper, HW2, [C1, C2].data
Apr 01	Class Cancelled
Apr 08	Unsupervised Learning I: Data Preprocessing & Scaling, Dimensionality Reduction, PCA, Factor Analysis, LWPR	Lecture IX	DimRed, LWPR
Apr 15	Unsupervised Learning II: Entropy, Info Max., KL divergence, ICA & Blind Separation	Lecture X	ICA paper
Apr 22	Inductive & Analytical Learning: Symbolic ML, EBG/EBL, Decision Trees Reinforcement Learning: Dynamic Programming, TD-learning, Q-Learning, REINFORCE, Actor-Critic	Lecture XI Lecture XII	HW3, [X,M].data, ica.m (HW3 : do not submit)
Apr 29	Final Project Presentations (40% Grades)	Project Guidelines (5-8 pm) Attendance Mandatory !!
May 06	Final Project Presentations (40% Grades)	Project Guidelines (5-8 pm) Attendance Mandatory !!