進行中 校際選修

115-1 選課時程

進行中

  • 初選第一階段 6/15 – 6/18
  • 初選第二階段 6/22 – 6/25
  • 校際選修 8/24 – 9/18
  • 初選第三階段 8/31 – 9/3
  • 開學後加退選 9/7 – 9/21
  • 逾期加退選 9/21 – 9/24
選課資源

應用多變量分析與機器學習

Applied Multivariate Analysis and Machine Learning

學期
113-1
學分
3 學分
當期課號
534006
永久課號
HSIE30073
開課單位
教育研究所
授課教師
吳俊育
校區
光復
類別
必修
上課時間表
週三
3
10:10–11:00
應用多變量分析與機器學習
HA216
3 節連堂
4
11:10–12:00
N
12:20–13:10

* 根據陽明交大上課時間表所列

概述

With the Project-based Learning, there are four major goals of this course: to understand the concepts related to Multivariate Analysis/Machine Learning; to be able to specify your own models and analyze the data using one of the Stat. programs; to be able to interpret the statistical findings to lay persons. We will be using the R program to perform the analyses.

先修科目

Students are expected to have basic knowledge on ANOVA, and Multiple Regression. Students who have not taken the required courses (e.g. Adv. Stats, IED 5895) have to meet with me before they register for this course.

教學方式

後課程搭配同步網路、非同步網路授課,課程連結如下:https://meet.google.com/hih-gpbw-eoo

評分方式

Homework Term project and final presentation Class presentation In-class and Facebook group participation Computer Lab and Experiments of multi-modal behavioral and psychological data analysis.

週次計畫
週次主題
第 1 週第一週為線上授課,請務必出席【授課教室:https://meet.google.com/hih-gpbw-eoo】Syllabus & Why Study Multivariate Analysis and Machine Learning in Substantive Research?
第 2 週L2:Multivariate Analysis of Variance
第 3 週L2:MANOVA[Disscussion and Case study]
第 4 週L3:Unsupervised ML &amp Cluster Analysis
第 5 週L3:Unsupervised ML &amp Cluster Analysis [Disscussion and Case study]
第 6 週L4:Canonical Correlation Analysis &amp Association Analysis
第 7 週L4:CCA&amp AA[Disscussion and Case study]
第 8 週L6&amp L7:Principle Component Analysis &amp Exploratory Factor Analysis
第 9 週Term Project Proposal
第 10 週L6&amp L7:PCA &amp EFA[Disscussion and Case study]
第 11 週L5:Supervised ML: Descriptive Discriminant Analysis, Random Forest, Support Vector Machine, Logistic Regression (NN)
第 12 週L7:Supervised ML: DDA, RF, SVM, Logistic Regreesion(NN)[Disscussion and Case study]
第 13 週Statistics Discussion全校運動會(停課)
第 14 週Oral Exam
第 15 週Project Preparation and Data Visualization
第 16 週Term Project Presentation (期末考週)
Office Hours
地點
TBA
時間
TBA
聯絡方式
分機:31843 Email:jiunyuwu@nycu.edu.tw