Summary of CPC251 PEMBELAJARAN MESIN DAN KECERDASAN KOMPUTAN (MACHINE LEARNING AND COMPUTATIONAL INTELLIGENCE)

Home Course Archive Course Search ePortfolio Mahara Helpdesk

THIS PORTAL IS ELEARN PORTAL ACADEMIC SESSION 2023/2024, FOR NEW ACADEMIC SESSION 2024/2025 PORTAL CLICK HERE

Dear Lecturers/Students,
This is eLearn@USM Portal - Academic Session 2023/2024.

Please do note the following opening date for eLearn@USM Portal - Academic Session 2024/2025:
Lecturers: 30 September 2024
Students: 07 October 2024

To go to eLearn@USM Portal - Academic Session 2024/2025, click here

CPC251 PEMBELAJARAN MESIN DAN KECERDASAN KOMPUTAN (MACHINE LEARNING AND COMPUTATIONAL INTELLIGENCE)

Lecturer: DR. MOHD NADHIR BIN AB WAHAB
Lecturer: PROFESOR MADYA DR. MOHD HALIM BIN MOHD NOOR

Skill Level: Beginner

General

Announcements

CPC251 Coursework Mark (13 July 2024, 18:10)

Webex Link

Feedback for 2nd Part of CPC251

Announcement

Course Planner

Course Planner

Group Registration

Group and Dataset Registration

Group x Dataset (Update: 14 April 2024 @ 20:00)

Group Registration

Project

Project Guideline, Rubric and Template

Datasets

Project Part 1 Submission (Due date: 17 May 2024 - 23:59)

Project Part 2 Submission (Due date: 7 July 2024 - 23:59)

Assignments

Assignment 1 (Guideline, Dataset and Template)

Assignment 1 (Due date: 13 May 2024)

Assignment 2 (Due date: 7 July 2024 @ 23:59)

Tests

Lab Resources

Python Tutorial

Download Anaconda

Lab 0 - Introduction to Jupyter Notebook

Lab 1 - Introduction to NumPy and Pandas

Lab 2 - Introduction to TensorFlow

Lab 2 - Introduction to TensorFlow (Updated)

Lab 3 - Supervised Learning

Lab 4 - Unsupervised Learning

Lab 5 - Neural Network (TensorFlow)

Lab 1 NumPy and Pandas (Recording)

Lab 4 Unsupervised Learning (Recording)

Lab 6 - Deep Learning

Lab 7 - Reinforcement Learning

Lab 8 - Fuzzy Logic

Lab 9 - Evolutionary Algorithm

Lab 9 - Webex Link (19/6/2024) @4:00 PM

Lab 10 - Swarm Intelligence

Introduction to Machine Learning & Supervised Learning

Slides: Introduction &amp; Supervised Learning

Loss Function (Notebook)

Confusion Matrix: TP, TN, FP and FN.

Confusion Matrix: Recall and Precision

Confusion Matrix: F1 Score

Linear Model

Slides: Linear Regression

Slides: Perceptron &amp; Logistic Regression

Linear Regression (Interactive Notebook)

Perceptron (Interactive Notebook)

Logistic Regression (Interactive Notebook)

Perceptron &amp; Logistic Regression (Recording)

Non-linear Model

Slides - k-Nearest Neighbors

Slides - Decision Tree

Slides - Support Vector Machine

Week 4 Recording

K-Nearest Neighbors (Interactive Notebook)

Decision Tree (Interactive Notebook)

Support Vector Machine (Interactive Notebook)

Unsupervised Learning

Slides - Clustering

k-Means (Interactive Notebook)

Agglomerative Clustering (Recording)

Neural Network

Slides - Neural Network

Neural Network (Interactive Notebook)

Intro to ANN (Recording)

Deep Learning

Notes - Deep Learning

Online Class Recording - Deep Learning Pt. 1

Online Class Recording - Deep Learning Pt. 2

Online Class Recording - Deep Learning Pt. 3

Deep Learning Quiz (22 May 2024)

Reinforcement Learning

Notes - Reinforcement Learning

Online Class Recording - Reinforcement Learning Pt. 1

Online Class Recording - Reinforcement Learning Pt. 2

Online Class Recording - Reinforcement Learning Pt. 3

Slides: Introduction & Supervised Learning

Slides: Perceptron & Logistic Regression

Perceptron & Logistic Regression (Recording)