Covers machine learning fundamentals through tree and unsupervised learning with hands-on Python labs.
Notices
The Ch04 multiple-choice quiz PDF is now available for review. Questions, answers, and explanations are included in the same file, and students can download it directly from the materials table and the assignments section below.
A supplementary PDF on softmax and cross-entropy was added to the Chapter 04 materials row. Students can use it as a review handout alongside the Week 6-7 classification lectures.
The Ch3 multiple-choice quiz PDF is now available for self-study. Questions, answers, and explanations are included in the same file, and students can download it directly from the materials table and the assignments section below.
The CH1-2 multiple-choice quiz PDF is now available for self-study. Questions, answers, and explanations are included in the same file, and students can download it directly from the assignments table and the shared materials row below.
Week 5-7 lecture materials are now linked as PDFs. The full pre-midterm range (Preview through Week 7) is currently published on this page.
Preview and Week 1-3 lecture materials (slides/notebook), plus the HW1 package, were synchronized from the data folder.
This semester covers CHAPTER 01-06. Deep learning chapters (Ch7-10) are not included this term.
Textbook, weekly plan, and grading criteria will be announced in the first session. Please set up Python (Anaconda or Google Colab) in advance.
Office hours are Mon/Tue 11:00-12:00 and Thu 12:00-13:00. Appointment is recommended.
Distributed as week1-assignment.zip. Complete assignment.ipynb, then upload your submission to LMS. 100 points, 5 problems.
Slides & Notebooks
| Week | Topic | Material |
|---|---|---|
| 1 | Course Introduction and Colab Setup | Slides |
| 2 | Ch 1 AI Overview — Markets and ML | Slides · Lecture Note · Ch1-2 Quiz/Answer PDF |
| 3 | Ch 1 Reinforcement and Colab Practice | |
| 4 | Ch 2 Working with Data — Train/Test, Preprocessing | Slides · Lecture Note |
| 5 | Ch 3 Regression and Regularization | Slides · Ch3 Quiz/Answer PDF |
| 6 | Ch 4 Classification (1) — Logistic Regression | Slides · Supplement: Softmax & Cross-Entropy · Ch4 Quiz/Answer PDF |
| 7 | Ch 4 Classification (2) — SGD Classifier | |
| 8 | Midterm | — |
| 9 | Ch 5 Tree Algorithms (1) — Decision Tree | To be uploaded |
| 10 | Ch 5 Tree Algorithms (2) — CV / Grid Search / Ensemble | To be uploaded |
| 11 | Ch 6 Unsupervised Learning (1) — Clustering, k-Means | To be uploaded |
| 12 | Ch 6 Unsupervised Learning (2) — PCA | To be uploaded |
| 13 | Vibe-Coding AI Project (1) — Topic and Planning | Project guide released in class |
| 14 | Vibe-Coding AI Project (2) — Implementation and Presentation | Final output submission and presentation |
| 15 | Final Exam | — |
| Shared | Quiz / Answer / Code Reference | Ch1-2 Quiz PDF with answers and explanations · Ch3 Quiz PDF with answers and explanations · Ch4 Quiz PDF with answers and explanations · Latest code note scheduled |
Evaluation & Tasks
| Component | Points | Rule |
|---|---|---|
| Midterm | 30 | Week 8 |
| Final | 30 | Week 15 |
| Quiz | 10 | |
| Final Project | 20 | Weeks 13-14 output and presentation |
| Attendance + Core Competency | 10 | Combined evaluation of attendance and class participation |
| No. | Title | Files | Submission | Status |
|---|---|---|---|---|
| HW1 | Fruit Classification with KNN (100 pts, 5 problems) | [week1-assignment.zip] | LMS upload (manual grading) | Active |
| Quiz | Ch 1–2 Multiple-Choice Quiz Review Sheet | Question/Answer/Explanation PDF | Self-study material | Available |
| Quiz | Ch 3 Multiple-Choice Quiz Review Sheet | Question/Answer/Explanation PDF | Self-study material | Available |
| Quiz | Ch 4 Multiple-Choice Quiz Review Sheet | Question/Answer/Explanation PDF | Self-study material | Available |
| Project | Vibe-Coding AI Project (Weeks 13-14) | Topic planning, implementation, and presentation | Class + final submission | Planned |
| Reference | Original Practice Code Repository | github.com/rickiepark/hg-mldl | Self-study | Always |
Local check for HW1: pytest tests/test_assignment.py -v. Follow variable names and file structure in README for grading compatibility.
Upload & Deadlines
| Item | Last Upload | Next Deadline | Note |
|---|---|---|---|
| Lecture Materials (Preview-Week 7) | 2026-03-30 | Pre-midterm range fully published | Added the Ch4 supplementary PDF link |
| HW1 | 2026-03-03 | 2026-03-17 23:59 | LMS upload (manual grading) |
| Quiz (CH4) | 2026-03-30 | Review PDF published | Questions, answers, and explanations included |
| Quiz (CH3) | 2026-03-28 | Review PDF published | Questions, answers, and explanations included |
| Quiz (CH1-2) | 2026-03-16 | Review PDF published | Questions, answers, and explanations included |
| Final Project | 2026-03-03 (plan) | Submission/Presentation in Weeks 13-14 | Topic guide distributed in class |
| Date | Category | Change |
|---|---|---|
| 2026-03-30 | Quiz | Uploaded the Ch4 multiple-choice quiz PDF |
| 2026-03-30 | Materials | Added the Ch4 Softmax/Cross-Entropy supplementary PDF link |
| 2026-03-28 | Quiz | Uploaded the Ch3 multiple-choice quiz PDF |
| 2026-03-15 | Materials | Added PDF links for the pre-midterm range (Weeks 5-7) |
| 2026-03-06 | Operations | Added upload/deadline/history tables |
| 2026-03-03 | Assignment | Published HW1 package and autograding guide |
| 2026-03-03 | Curriculum | Confirmed semester scope as CH1-6 only |
| 2026-02-28 | Materials | Linked Preview and Week 1-3 files |
Course Inquiry
Office: Convergence Science Bldg. 2F, Room 24221 (Ext. 2561)
Email: sangdonpark@dju.kr
Office Hours: Mon/Tue 11:00-12:00, Thu 12:00-13:00 (appointment recommended)
Email subject format: [AI][Student ID] Topic