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

機器學習

Machine Learning

學期
106-1
學分
3 學分
當期課號
5088
永久課號
ECM9032
開課單位
電信工程研究所
授課教師
簡仁宗
校區
光復
類別
選修
上課時間表
週五
5
13:20–14:10
機器學習
ED219
3 節連堂
6
14:20–15:10
7
15:30–16:20

* 根據陽明交大上課時間表所列

概述

Machine learning, a branch of artificial intelligence, is a scientific discipline concerned with the design and development of algorithms that allow computers to evolve behaviors based on empirical data from sensor data or databases. A major focus is to automatically learn to recognize complex patterns and make intelligent decisions based on data. This course shall deliver fundamental theories of machine learning which can be applied for many intelligent information systems.

先修科目

Calculus, Linear Algebra, Probability & Statistics

教學方式

Lecture notes and slides will be provided. Teacher assistants (廖偉翔, 廖尉琳, 廖勇冠, 王俊煒, 郭俊麟, 郭哲宇, 呂昱穎, 郭子聖) are available at PM 19:30-20:30 in ED 912 in week days.

評分方式

Midterm Exam (30%), Final Exam (40%), Homework (30%), Class Attendance (10%)

課程大綱
週次計畫
週次主題
第 1 週Introduction to Machine Learning
第 2 週Curve Fitting & Model Selection
第 3 週Decision Theory & Information Theory
第 4 週Probability Functions - Binomial, Multinomial, Beta, Dirichlet, Gaussian & Student t Distributions
第 5 週Generative Models - Least Squares & Regularized Least Squares, Maximum Likelihood, Maximum a Posteriori
第 6 週Bayesian Linear Regression, Bayesian Model Comparison & The Evidence Framework
第 7 週Discriminant Function - Least Squares, Fisher's Discriminant & Perceptron Algorithm
第 8 週Discriminative Model - Logistic Regression, Laplace Approximation & Bayesian Logistic Regression
第 9 週Midterm Exam & Homework
第 10 週Kernel Methods
第 11 週Gaussian Process
第 12 週Sparse Kernel Methods
第 13 週Support Vector Machine
第 15 週Mixture Models and EM
第 15 週Relevance Vector Machine
第 16 週Hidden Markov Models
第 17 週Approximate Inference
第 18 週Final Exam & Homework
教科書

1. C. M. Bishop, Pattern Recognition and Machine Learning, Springer, 2006. 2. S. Watanabe and J.-T. Chien, Bayesian Speech and Language Processing, Cambridge University Press, 2015.

Office Hours
地點
ED912
時間
PM17:00-PM18:00 on Monday
聯絡方式
jtchien@nctu.edu.tw