98年第2學期-4436 人工智慧方法論（二） 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 report	30
Final report	30

教育目標

Learning is an alternative in pursuing the goal. In this semester, two major topics will be covered: Statistical Learning Theory (SLT) and Graphical models, sometimes noted as Bayesian Network (BN).

課程概述

This course is designed for the Ph.D. or aggressive 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. In this semester, two major topics will be covered: Statistical Learning Theory (SLT) and Graphical models, sometimes noted as Bayesian Network (BN).

基本資料

選修課，學分數：0-3
上課時間：三/6,7,8[E232]
修課班級：工工碩博
修課年級：年級以上
選課備註：B737

參考書目

Vapnik, V., “The Nature of Statistical Learning Theory”, Springer, 1999