머신러닝을 위한 기초 수학 및 프로그래밍 실습
Basic Mathematics and Programming Practice for Machine Learning
M2177.005800
This course aims to develop an understanding of how wise judgment becomes possible in complex phenomena. Students learn how to capture the internal order of phenomena through mathematics and implement it through programming as a sequence of logical procedures. Mathematics is treated as a language for clearly describing complex phenomena, while programming serves as a cognitive tool that translates such descriptions into executable judgment and action. Just as humans perceive the world and make decisions through language, the course explores how language can be modeled as states, probabilities, and decision-making structures, and how these models can be extended into agent-based machine learning systems. Students work with real-world data drawn from natural, industrial, and medical domains, gaining experience in connecting abstract theory to practical problems. In particular, by approaching challenges that are difficult to solve individually through team-based projects with students from diverse academic backgrounds, students experience how different perspectives can be integrated into a coherent judgment structure. The course is open to students of all majors and emphasizes the use of mathematics and programming as tools for structured thinking. Through this course, students are expected to develop the ability to logically analyze and solve complex problems, and to creatively apply mathematical and computational methods to a wide range of real-world challenges.
- Location: Bld 43-101
- Lecture: Friday 9:00 - 12:00
Instructor
Teaching Assistants
Grading
- Attendance: 5%
- Assignment: 40%
- Final exam: 30%
- Final project: 15%
- Final report: 5%
- Attitude: 5%
Assignments
- homeworks: TBD
Lecture Schedule
| Week | Date | Lecture |
|---|---|---|
| 1 | 3/6 | Axiomatic Systems and the Foundations of Thought Introduction to axiomatic systems as the foundation of reasoning, from the structure of the universe to the structure of human thought. |
| 2 | 3/13 | Observation, Misinterpretation, and Judgment Retrograde motion, derivatives, and chain rules as metaphors for how local observations can lead to global misinterpretations in judgment. |
| 3 | 3/20 | Optimization and Judgment Optimization frameworks, gradient descent, convexity, and Monte Carlo methods. |
| 4 | 3/27 | Geometric Thinking and Simplicity Analytical geometry, neural modeling, and Occam’s razor. Activity: Team Meeting #1 |
| 5 | 4/3 | Linear Algebra, Meaning, and Associative Memory Vectors, matrices, and associative memory as mathematical foundations for meaning and recall. |
| 6 | 4/10 | Dimensionality Reduction and Selective Attention Reducing complexity to enable effective judgment, information compression, and feature selection. |
| 7 | 4/17 | Perspective and Interpretation Eigenvectors, PCA, and SVD as changes of perspective that affect interpretation and decision making. |
| 8 | 4/24 | Distance, Similarity, and Language Distance metrics in general spaces, autoencoders, and the role of distance in linguistic and conceptual similarity. Assignment: One-page project idea proposal |
| 9 | 5/1 | Randomness and Rationality under Uncertainty Gaussian distributions and the strategic role of randomness in decision making. |
| 10 | 5/8 | Distance in Probability and Divergent Judgments Kullback–Leibler divergence, decision trees, ensemble methods, and comparing different decision strategies. Activity: Project planning |
| 11 | 5/15 | Written Exam Activity: Team Meeting #2 |
| 12 | 5/22 | Time, Memory, and Prediction Decision making over time, temporal distance, and the role of memory in judgment. |
| 13 | 5/29 | Symmetry, Intelligence, and Incompleteness Symmetry in machine learning, recommendation systems, and fundamental limits of intelligence and reasoning. |
| 14 | 6/5 | Peer Review and Project Refinement Peer-to-peer evaluation of decision-making structures and agent designs. |
| 15 | 6/12 | Final Project Presentation Presentation and demonstration of team projects focusing on judgment structure, agent behavior, and explainability. |
Final PT
- XAICON 2026 [TBA]
- XAICON 2023
- XAICON 2022
- XAICON 2021
- XAICON 2020
- XAICON 2019