Course description:
The course provides an introduction to machine learning. The course will provide an
overview to machine learning ranging from statistical-based method, kernel based
method, to contemporary deep learning method. It also includes hands-on exercises.

Textbook:
Introduction to Machine Learning, Fourth Edition, Ethem Alpaydin

Teaching Method:
Lecture

Syllabus (Tentative):
Section 1
Introduction to Machine Learning
Supervised Learning
Bayesian Decision Theory
Parametric Model
Multivariate Methods

Section 2
Clustering/Dimension Reduction
Decision tree
Linear Discrimination
Support Vector Machine

Section 3
Multilayer Perceptron
Deep learning
Design and Analysis of Machine Learning Experiment


Grading (Tentative):
3 Homework (13% each)
1 Midterm (20%)
1 Final (35%)
Hand-on exercise (6%)


Website:
We will use eelearn