Course Code/Name : MSG 332 Introduction to Machine Learning
No. of Units : 4
Prerequisite : MAT181, MAT111, MAT263
Lecture Time / Venue : Monday, 10:00 – 11:50 / BT204,PPSM
Friday, 10:00 – 11:50 / Lab 1, PPSM
Instructor : Assoc. Prof. Dr. Gobithaasan Rudrusamy
Email : gobithaasan@usm.my
Office : Room 025 (GR)
Phone : 04-6534766 (GR)
Telegram Group https://t.me/+njAKZQXmHtozYjA1
COURSE SYNOPSIS
This course introduces fundamental knowledge and techniques of supervised and unsupervised machine learning. Topics such as linear and logistic regression, Naive Bayes, Support Vector Machines (SVM), decision tree, clustering and neural network will be covered in this course. Students are expected to obtain hands-on experience during practical to address real world problems using a suitable programming language.
No. of Units : 4
Prerequisite : MAT181, MAT111, MAT263
Lecture Time / Venue : Monday, 10:00 – 11:50 / BT204,PPSM
Friday, 10:00 – 11:50 / Lab 1, PPSM
Instructor : Assoc. Prof. Dr. Gobithaasan Rudrusamy
Email : gobithaasan@usm.my
Office : Room 025 (GR)
Phone : 04-6534766 (GR)
Telegram Group https://t.me/+njAKZQXmHtozYjA1
COURSE SYNOPSIS
This course introduces fundamental knowledge and techniques of supervised and unsupervised machine learning. Topics such as linear and logistic regression, Naive Bayes, Support Vector Machines (SVM), decision tree, clustering and neural network will be covered in this course. Students are expected to obtain hands-on experience during practical to address real world problems using a suitable programming language.
Skill Level: Beginner