ADVANCED MACHINE LEARNING

Instructor: Elizer Ponio Jr

Email: [email protected]

Consultation Hours: Send me a message in MS Teams 🙂

Credits: 3.0 units

Time Allotment: 2.67 hours lecture every week

4.00 hours laboratory every week

Course Description

This course is a continuation of CCMACLRL – Introduction to Machine Learning. This course covers unsupervised learning techniques to train machine learning models for different tasks. Topics to be covered include feature selection algorithms, clustering algorithms, principal component analysis and association rule learning.

Pre-requisites for this class

• Proficiency in one programming language. All class assignments will be in Python. If you have a lot of programming experience but in a different language (e.g. Javascript/Java) you will probably be fine.
• College Calculus, Linear Algebra. You should be comfortable taking derivatives and understanding matrix vector operations and notation.
• Basic Probability and Statistics. You should know basics of probabilities, Gaussian distributions, mean, standard deviation, etc.
• CCMACLRL – Introduction to Machine Learning

Course Outcomes

By the end of the class students should be able to:

• Understand the strengths and weaknesses of many popular unsupervised machine learning approaches.
• Appreciate the underlying mathematical relationship within and across unsupervised ML algorithms and the paradigms of unsupervised learning.
• Implement various unsupervised ML algorithms in a range of real-world application by writing a publishable paper.

Class Policies

1. Attendance is necessary for each student to obtain maximum benefits for instruction, 80% attendance or 69 hours for one trimester is required.
2. Failure to wear complete uniform will be considered an absence and the student will not be allowed to take any examination.
3. Special examination is only given for excused absences. Excuse letter duly signed by the parents/guardian or a medical examination (in case of sickness) is required.
4. Students may bring their cellular phones to class provided these are placed on silent mode. These should not be used during class hours except during extreme necessities. Cellular phones should be switched off during examinations.
5. Students should be in complete uniform and exam permit should be presented during major examinations.