機率
Probability
| 節 | 週三 | 週五 |
|---|---|---|
3 10:10–11:00 | 機率 EC022 2 節連堂 | |
4 11:10–12:00 | ||
7 15:30–16:20 | 機率 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)
Homeworks: 40% (including written and programming tasks) Midterm: 30% Final Exam: 30%
| 週次 | 主題 |
|---|---|
| 第 1 週 | Probability model, axioms of probability, and continuity of probability |
| 第 2 週 | Conditional probability and independence |
| 第 3 週 | Review of combinatorial methods Discrete random variables |
| 第 4 週 | Distribution functions Special parametric discrete distributions (Bernoulli, binomial, and Poisson) |
| 第 5 週 | Continuous random variables |
| 第 6 週 | Special parametric continuous distributions (e.g., uniform, normal, and exponential) |
| 第 7 週 | Bivariate and multivariate distributions |
| 第 8 週 | Midterm exam |
| 第 9 週 | Bivariate normal Moment generating functions |
| 第 10 週 | Sums of independent random variables and limit theorems |
| 第 11 週 | Sums of independent random variables Concentration inequalities |
| 第 12 週 | Law of large numbers |
| 第 13 週 | Law of large numbers Central limit theorem |
| 第 14 週 | Maximum likelihood estimation Maximum a posteriori estimation |
| 第 15 週 | Markov chain |
| 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
- Office hour: T
- 聯絡方式
- pinghsieh@nycu.edu.tw