98年第1學期-4436 人工智慧方法論 課程資訊

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

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.

基本資料

選修課，學分數：3-0
上課時間：二/2,3,4[E232]
修課班級：工工碩博1
修課年級：年級以上
選課備註：B637

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