機器學習概論
Introduction to Machine Learning
學期
113-1
學分
3
學分
當期課號
515520
永久課號
CSCS20024
開課單位
資訊學院共同課程
授課教師
胡毓志
校區
光復
類別
選修
上課時間表
| 節 | 週二 |
|---|---|
5 13:20–14:10 | 機器學習概論 EC022 3 節連堂 |
6 14:20–15:10 | |
7 15:30–16:20 |
* 根據陽明交大上課時間表所列
概述
This is a course aimed to provide an foundation of advanced grad-level courses, e.g. machine learning and data mining.
先修科目
Computer Programming, Data Structures, Introduction to Algorithms
教學方式
Onsite lectures + lecture notes
評分方式
Only tentative: a. Quiz (20%); b. Mid-term (30%) and Final (30%); c. Term Project(s) (20%)
週次計畫
| 週次 | 主題 |
|---|---|
| 第 1 週 | Introduction:1. Why machine learning2. Concept learning3. Inductive Learning |
| 第 2 週 | Data Preparation:1. Data types2. Data quality 3. Data preprocessing |
| 第 3 週 | Modeling:1. Parametric models2. Non-parametric models |
| 第 4 週 | Decision tree learning:1. Tree construction2. Tree pruning3. From trees to rules |
| 第 5 週 | Bayesian learning1. Bayesian decision2. Naive Bayes |
| 第 6 週 | Neural Nets:1. Perceptron2. Multilayer perceptrons3. Backprop |
| 第 7 週 | Clustering:1. Partition-based 2. Density-based clustering |
| 第 8 週 | Evaluation:1. Methodology2. Performance measures |
| 第 9 週 | Other issues:1. Algorithm-centric vs. Data-centric2. Predictive performance vs. comprehensibility |
| 第 10 週 | |
| 第 11 週 | |
| 第 12 週 | |
| 第 13 週 | |
| 第 14 週 | |
| 第 15 週 | |
| 第 16 週 |
教科書
1. Machine Learning by Tom M. Mitchell, 1997. 2. Machine Learning for predictive data analytics by Kelleher, Namee, D’Arcy, 2015. 3. Introduction to Machine Learning by Alpaydin, 2020.
Office Hours
- 地點
- EC332C
- 時間
- Mon 9~10AM
- 聯絡方式
- By appointment