數值分析
Numerical Method
學期
113-2
學分
3
學分
當期課號
132305
永久課號
BEBE20014
開課單位
生物醫學工程學系
授課教師
鄔蜀威
校區
陽明
類別
選修
上課時間表
| 節 | 週三 |
|---|---|
2 09:00–09:50 | 數值分析 YEA200 3 節連堂 |
3 10:10–11:00 | |
4 11:10–12:00 |
* 根據陽明交大上課時間表所列
概述
Numerical analysis is the study of numerical algorithms that attempt to find approximate solutions of problems rather than the exact ones. Numerical method finds application in all fields of engineering and the physical sciences, and in the 21st century also the life and social sciences like economics, medicine, business and even the arts. Furthermore, artificial intelligence (AI) has revolutionized numerous industries by providing intelligent solutions to complex problems, and numerical method plays a pivotal role in enhancing the performance and reliability of AI algorithms.
評分方式
Attendance Rate 30% Midterm Exam 30% Final Exam 40%
週次計畫
| 週次 | 主題 |
|---|---|
| 第 1 週 | 1. Introduction 2. Errors 3. The Taylor series |
| 第 2 週 | 1. Solutions of equations of one variable 2. Interpolation and curve fitting--polynomial approximation |
| 第 3 週 | 1. Interpolation and curve fitting--parametric equations and curves |
| 第 4 週 | 1. Solution of simultaneous linear algebraic equations 2. Numerical integration |
| 第 5 週 | 1. Numerical differentiation 2. Introduction to cryptography |
| 第 6 週 | 1. Modern cryptography |
| 第 7 週 | 1. Hash function |
| 第 8 週 | 1. Midterm Exam 2. Introduction to AI and ML |
| 第 9 週 | 1. Feature engineering 2. Loss function |
| 第 10 週 | 1. Optimization |
| 第 11 週 | 1. Regression analysis |
| 第 12 週 | 1. Algorithms of supervised learning (I) |
| 第 13 週 | 1. Algorithms of supervised learning (II) |
| 第 14 週 | 1. Algorithms of unsupervised learning 2. Principal component analysis |
| 第 15 週 | 1. Reinforcement learning |
| 第 16 週 | Final Exam |
教科書
Textbook not required