MACHINE LEARNING (4 Credits)

Learning Outcomes:

On successful completion of this course, student will be able to: LO1 – explain the fundamental of machine learning concept; LO2 – interpret the distribution of dataset using regression method; LO3 – experiment classification and clustering algorithm from given dataset.

Topics:

1. Introduction to Machine Learning;
2. Exploratory Data Analysis and Preprocessing Data;
3. Linear Regression;
4. Logistic Regression;
5. Model Selection and Regularization;
6. Naive Bayes;
7. Recommender System;
8. Decision Tree and Ensemble Learning;
9. Support Vector Machine;
10. Clustering;
11. Dimensionality Reduction;
12. Machne Learning Operations;
13. Review and Presentation.