98年第1學期-4436 人工智慧方法論 課程資訊

iLearn 公告清單

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Teams 連結清單

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評分方式

評分項目 配分比例 說明
Homework 20
Participation in the classes 20
Midterm project 30
Final project 30

選課分析

本課程名額為 70人,已有15 人選讀,尚餘名額55人。

授課教師

王偉華

教育目標

This course is designed for the Ph.D. and aggresive Master students. The purpose of this course is to help the students mastering the theoretical concepts and skills in analyzing the learning processes and the related methodologies. The ways to expolore the relationships among data are heavily investigated and discussed in these years. Learning is an alternative in pursuing the goal. The basic concepts of Machine Learning will be covered and the methodologies on the statistical notion on data modeling will be emphasized.

課程概述

This course is designed for the Ph.D. or aggresive Master students. The purpose of this course is to help the students to have acquaintance with the theoretical concepts and methodologies in the Statistical Learning Theory (SLT). The ways to expolore the relationships among data attracts many research attentions in these years. SLT is a heavy investigated, both in theory and methodologies, alternative in pursuing the target.

課程資訊

參考書目

1. Vapnik, V., “The Nature of Statistical Learning Theory”, Springer, 1999
2. Jordan, I. Michael, “Learning in Graphical Models”, MIT press, 1999