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敏求學院課程(Miin Wu School of Computing)
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  Course Description/課程描述:

Machine Learning is a popular research area lately. The main goal is to investigate the high dimensional, large amount or complex data, and to develop the useful algorithms to discover information within data.


  Course Objectives/課程目標: 

1. Introduce different methods in Machine Learning.

2. Student is ability to analyze massive and complicate data.

3. Student is capable to do programming based on the different algorithms. 

  Course Content/課程內容: 

Week 01:Introduction

Week 02:Statistical Learning

Week 03:Linear Regression

Week 04:Linear Regression

Week 05:Linear Regression

Week 06:Classification

Week 07:Classification

Week 08:Classification

Week 09:Resampling Methods

Week 10:Resampling Methods

Week 11:Linear Model Selection and Regularization

Week 12:Linear Model Selection and Regularization

Week 13:Tree-Based Methods

Week 14:Tree-Based Methods

Week 15:Support Vector Machines

Week 16:Support Vector Machines

Week 17:Deep Learning 

Week 18:Deep Learning 

    Textbook/教科書:

An Introduction to Statistical Learning with Applications in R 2nd Edition, By Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani

 Grading Policy/評量方式:

1. Term Project Report or fincal exam 40%

2. Homework    60%