MACHINE LEARNING (4 Credits)

Learning Outcomes:

On successful completion of this course, student will be able to:

1. Explain the fundamental of machine learning concept
2. Interpret the distribution of dataset using regression method
3. Experiment classification and clustering algorithm from given dataset

Topics:

1. Introduction to Machine Learning 1
2. Introduction to Machine Learning 2
3. Probability and stochastic processes 1
4. Probability and stochastic processes 2
5. Learning in parametric modeling 1
6. Learning in parametric modeling 2
7. Mean-Square Error linear estimation
8. Feature Engineering: Feature Extraction & Selection
9. The nearest neighbor rule (KNN) & Logistic regression
10. Support Vector Machine
11. Classification Tree
12. Clustering
13. Review & project presentation