Course description:
The course provides an introduction to machine learning. The course will provide
an overview to machine learning ranging from statistical-based method,
discriminant-based method, multi-layer perceptron 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
Invited Lecture
Nvidia DLI – Hands on lecture
Website:
We will use eelearn