課程資訊
課程名稱
數值線性代數
Numerical Linear Algebra 
開課學期
110-1 
授課對象
理學院  數學研究所  
授課教師
王偉仲 
課號
MATH5411 
課程識別碼
221 U4210 
班次
 
學分
3.0 
全/半年
半年 
必/選修
選修 
上課時間
星期四2,3,4(9:10~12:10) 
上課地點
天數202 
備註
總人數上限:40人 
Ceiba 課程網頁
http://ceiba.ntu.edu.tw/1101nla 
課程簡介影片
 
核心能力關聯
本課程尚未建立核心能力關連
課程大綱
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課程概述

課程網站請見:https://sites.google.com/view/nla2021 

課程目標
T課程網站請見:https://sites.google.com/view/nla2021 
課程要求
課程網站請見:https://sites.google.com/view/nla2021 
預期每週課後學習時數
 
Office Hours
另約時間 
指定閱讀
[S] "Linear Algebra and Learning from Data" by Gilbert Strang, ISBN: 9780692196380, 2019
https://ocw.mit.edu/courses/mathematics/18-065-matrix-methods-in-data-analysis-signal-processing-and-machine-learning-spring-2018/index.htm

[BV] "Introduction to Applied Linear Algebra – Vectors, Matrices, and Least Squares" by Stephen Boyd and Lieven Vandenberghe
http://vmls-book.stanford.edu/

[TB] "Numerical Linear Algebra" by Lloyd N. Trefethen and David Bau III, SIAM 
參考書目
Required

[S] "Linear Algebra and Learning from Data" by Gilbert Strang, ISBN:
9780692196380, 2019
https://ocw.mit.edu/courses/mathematics/18-065-matrix-methods-in-data-analysis-
signal-processing-and-machine-learning-spring-2018/index.htm

[BV] "Introduction to Applied Linear Algebra – Vectors, Matrices, and Least
Squares" by Stephen Boyd and Lieven Vandenberghe
http://vmls-book.stanford.edu/

[TB] "Numerical Linear Algebra" by Lloyd N. Trefethen and David Bau III, SIAM

Optional

"Mathematics for Machine Learning" by Marc Peter Deisenroth, A. Aldo Faisal, and
Cheng Soon Ong, 2020 (https://mml-book.com)

"Linear Algebra for Everyone" by Gilbert Strang, ISBN 978-1-7331466-3-0, 2020

"Applied Numerical Linear Algebra" by James W. Demmel, SIAM, 1997

"Matrix Computations", Fourth Edition, Gene H. Golub and Charles F. Van Loan,
SIAM, 2013

Iterative Methods for Sparse Linear Systems, 2nd Edition, Yousef Saad, 2003
(http://www-users.cs.umn.edu/~saad/IterMethBook_2ndEd.pdf)

Templates for the Solution of Linear Systems: Building Blocks for Iterative
Methods, 2nd Edition, Richard Barrett et al., SIAM, 1994

大型線性系統與特徵值問題 http://ocw.lib.ntnu.edu.tw/course/view.php?id=190  
評量方式
(僅供參考)
 
No.
項目
百分比
說明
1. 
Homework 
30% 
 
2. 
Midterm 
30% 
 
3. 
Project 
30% 
 
4. 
課堂討論,課堂報告 
10% 
 
 
課程進度
週次
日期
單元主題