機率(英文授課)
Probability
| 節 | 週三 | 週五 |
|---|---|---|
3 10:10–11:00 | 機率(英文授課) EC022 2 節連堂 | |
4 11:10–12:00 | ||
7 15:30–16:20 | 機率(英文授課) EC022 |
* 根據陽明交大上課時間表所列
This course is designed to equip students with the useful tools of probability theory and the basic understanding of its applications, such as machine learning and communication networking.
1. An undergraduate-level understanding of calculus is assumed 2. Programming skills in a high-level language (e.g. python or MATLAB)
TBD
Homeworks: 40% (6 assignments, including written and programming tasks) Midterm: 30% Final Exam: 30%
| 週次 | 主題 |
|---|---|
| 第 1 週 | Axioms of probability Review of combinatorial methods |
| 第 2 週 | Review of combinatorial methods (cont.) Conditional probability and independence |
| 第 3 週 | Discrete random variables Distribution functions |
| 第 4 週 | Special parametric discrete distirbutions (Bernoulli, Binomial, and Poisson) |
| 第 5 週 | Continuous random variables |
| 第 6 週 | Special parametric continuous distributions (uniform, Normal, exponential, Gamma, and Beta) |
| 第 7 週 | Bivariate and multivariate distributions |
| 第 8 週 | Midterm exam |
| 第 9 週 | MGF and Concentration Inequalities |
| 第 10 週 | Sums of independent random variables and limit theorems |
| 第 11 週 | Sums of independent random variables and limit theorems |
| 第 12 週 | MLE and MAP |
| 第 13 週 | Markov Chain |
| 第 14 週 | Markov Chain and Sampling methods |
| 第 15 週 | Sampling methods |
| 第 16 週 | Final exam |
Textbook: - Saeed Ghahramani, Fundamentals of Probability with Stochastic Processes, 4th ed., CRC Press, 2018. Other references: - Dimitri P. Bertsekas and John N. Tsitsiklis, Introduction to Probability, 2nd ed., Athena Scientific, 2002. - Sidney I. Resnick, A Probability Path, Springer Science & Business Media, 2013.
- 地點
- EC713
- 時間
- TBD
- 聯絡方式
- pinghsieh@nctu.edu.tw