114年第2學期-1028 機器學習導論 課程資訊
評分方式
| 評分項目 | 配分比例 | 說明 |
|---|---|---|
| Exam | 25 | |
| Regular Assignments | 30 | |
| Final Project | 25 | |
| Attendance Rate | 20 |
選課分析
本課程名額為 60人，已有0 人選讀，尚餘名額60人。
本課程可網路登記，目前已登記人數為 16 人，選上機率為99.9%
登入後可進行最愛課程追蹤 [按此登入]。
授課教師
陳仕偉教育目標
The goal of this course is to provide students with the skills to learn machine learning techniques, enabling them to quickly and systematically grasp the latest trends in artificial intelligence technology and thoroughly understand how artificial intelligence works.
The course will first cover the theory of machine learning, including classification, problem definition, and methods. It will then delve into the important concepts of neural networks, which are at the core of machine learning. This will be accompanied by hands-on examples and self-practice, ensuring not only a deep understanding of the theory but also the practical implementation of neural networks.
課程資訊
基本資料
選修課，學分數：0-3
上課時間：五/2,3,4[ST436]
修課班級：資工系3,4
修課年級：3年級以上
選課備註：工院0744課程併班
教師與教學助理
授課教師：陳仕偉
大班TA或教學助理：尚無資料
Office HourFriday 13:00-14:00 / ST426
授課大綱
授課大綱：開啟授課大綱(授課計畫表)
(開在新視窗)
參考書目
1.Self-made teaching materials
2.Deep Learning/ ISBN:0262035618/ MIT
3.Pattern Recognition and Machine Learning/ISBN:0387310738 /Springer
開課紀錄
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