機器學習概論
Introduction to Machine Learning
| 節 | 週二 |
|---|---|
5 13:20–14:10 | 機器學習概論 EDB27 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
This course introduces a detailed and focused treatment of the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications. Technical and mathematical material is augmented with explanatory worked examples, and case studies illustrate the application of these models in the broader business context. 欲加簽者請開學第一周再來
Linear algebra, statistics, probability, and computer programming 請注意,修課人數滿180人就不再加簽 請照學校建議方式加簽 (二) 該課程於特殊狀況下,開放書面加退選。學生請先填寫『網路選課加退選 處理表』,再將申請表Email給「任課老師」,並詢問「任課老師」是否同意加退選。 1. 任課老師同意後可直接至「課務管理系統-選課系統」-「課程維護」-「維護」-幫 學生加退選。(詳細操作如下) 2. 或請學生將「任課老師」同意簽章的申請表Email或送交「主開課單位」助理協助 處理。 注意!!本學期第一次上課(9/14)會以Google Meet進行: https://meet.google.com/ctw-hfha-khx 老師當天不會在教室,請不要前來教室! We will use Google Meet for the first week (9.14). https://meet.google.com/ctw-hfha-khx Although I will be the classroom at that time, don't come to the classroom except you have a requirement for joining this course.
6 homework: 50% 1 Term projects: 50%
| 週次 | 主題 |
|---|---|
| 第 1 週 | Google Meet: https://meet.google.com/ctw-hfha-khx Machine Learning for Predictive Data Analytics |
| 第 2 週 | Data to Insights to Decisions |
| 第 3 週 | Probability-based Learning |
| 第 4 週 | Probability-based Learning |
| 第 5 週 | Information-based Learning |
| 第 6 週 | Information-based Learning |
| 第 7 週 | Similarity-based Learning |
| 第 8 週 | Similarity-based Learning |
| 第 9 週 | Error-based Learning |
| 第 10 週 | Error-based Learning |
| 第 11 週 | Error-based Learning |
| 第 12 週 | Unsupervised learning |
| 第 13 週 | Unsupervised learning |
| 第 14 週 | Introduction to deep learning |
| 第 15 週 | Final project demonstration |
| 第 16 週 | Final project demonstration |
John D. Kelleher, Brian Mac Namee and Aoife D'Arcy, "Fundamentals of Machine Learning for Predictive Data Analytics, Second Edition," MIT Press, 2021. Aurélien Géron, "Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems," 2nd, O'Reilly Media, 2019. Mehryar Mohri, Afshin Rostamizadeh, and Ameet Talwalkar, "Foundations of Machine Learning," MIT Press, Second Edition, 2018.
- 地點
- EC444, CS331
- 時間
- By appointment
- 聯絡方式
- ytc@cs.nctu.edu.tw jameschengcs@nycu.edu.tw