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

機率

Probability

學期
112-1
學分
3 學分
當期課號
515512
永久課號
CSCS10007
開課單位
資訊學院共同課程
授課教師
謝秉均
校區
光復
類別
必修
上課時間表
週三
週五
3
10:10–11:00
機率
ED117
2 節連堂
4
11:10–12:00
7
15:30–16:20
機率
ED117

* 根據陽明交大上課時間表所列

概述

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.

先修科目

1. An undergraduate-level understanding of calculus is assumed 2. Programming skills in a high-level language (e.g. python or MATLAB)

評分方式

Homeworks: 40% (including written and programming tasks) Midterm: 30% Final Exam: 30%

週次計畫
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 methodsDiscrete random variables
第 4 週Distribution functionsSpecial 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 normalMoment generating functions
第 10 週Sums of independent random variables and limit theorems
第 11 週Sums of independent random variablesConcentration inequalities
第 12 週Law of large numbers
第 13 週Law of large numbersCentral limit theorem
第 14 週Maximum likelihood estimationMaximum a posteriori estimation
第 15 週Markov chain
第 16 週Final exam
教科書

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.

Office Hours
地點
EC418
時間
Office hour: TBD
聯絡方式
pinghsieh@nycu.edu.tw