Summary of CDS503 PEMBELAJARAN MESIN (MACHINE LEARNING)

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General

Course Planner - Semester 2, 2024/2025 (F2F)

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Announcements

Tests

TEST 1

TEST 2

Group Project

Group Project Guidelines

Group Project: Interactive Poster Presentation Instructions

Group Project: Discussion

Group Formation Padlet Wall

Group Project: Group Selection

Group Project: Proposal Template

Group Project: Proposal Grading Rubric

Project Proposal Submission

Group Project: Final Report Template

Group Project: Final Report Grading Rubric

Final Report Submission

Group Project: Presentation Grading Rubric

Interactive Poster @ Padlet

Assignments

Task 1: Data Collection Task Description

Emotion Data Collection Form

Assignment: Data Collection Submission

Depression Risk and Social Media Use Survey

Assignment 1 Task Description

Data

Assignment 1: Grading Rubric

Assignment 1 Submission

Assignment 1: Run Model Test Set Instructions

Assignment 1 Test Set

Assignment 1: Model Testing

Assignment 2 Task Description

Data

Assignment 2: Grading Rubric

Assignment 2: Submission

Week 1: Introduction

Week 1 Live Lecture: Video Recording

Course Information

Week 1: Lecture Slides

AutoDraw

Quick, Draw!

Semantris

Dhar: Data Science and Prediction

Jordan &amp; Mitchell: Machine learning: Trends, Perspectives, and Prospects

Week 1: Discussion

Week 2: Machine Learning Basics & Supervised Learning

Week 2: Housekeeping

Week 2: Lecture Slides

Week 2 Video Lecture: Supervised Learning

Week 2: Discussion

Week 3: Classification (Overview)

Week 3: Housekeeping

Week 3: Lecture Slides

Week 3 Video Lecture: Classification

Python Installation and Setup: Guide

Lab 01

Lab 01 Exercise Submission

Week 4: Classification (KNN and Decision Trees)

Week 4: Housekeeping

Week 4: Lecture Slides

Lab 02

Lab 02 Submission

Class Activity: Decision Trees

Dark Side Decision Tree Submission

Week 5: Classification (Bayesian Classifiers and Support Vector Machines)

Week 5: Lecture Slides

Bayesian Classifiers Practice Quiz

Week 5 SVM Video Lecture

Lab 03

Lab 03 Submission

Week 6: Classification (ML Experiment Design)

Week 6: Lecture Slides

Video: Understanding Feature Space

Week 7: Regression

Week 7: Lecture Slides

Week 7: Review Quiz

Week 7: Discussion

Lab 04

Jordan & Mitchell: Machine learning: Trends, Perspectives, and Prospects

Optional Reading: Wrappers for feature subset selection (Kohavi & John, 1997)