機率學(Probability)自20世紀起一直是各類應用工程非常重要的領域知識，近年更大量應用至AI領域的模型建置。
在電腦承擔大量運算以及套裝軟體或程式簡化操作過程的現代，學習機率學有助於學員理解以及解構問題本身。
進而選擇並正確使用數學模型、AI工具、套裝軟體以及最後的結果呈現
本課程預期在在一學期的時間內教授以下內容
1.試驗、模型與機率
2.隨機變數(離散、連續)
3.條件機率與相關AI模型
部分課程將搭配 python/matlab/excel範例Probability has been a very important field of knowledge in various types of applied engineering since the 20th century. In recent years, it has been increasingly used in model construction in the AI field.
In an era where computers are responsible for a large number of calculations and software packages or programs simplify the operation process, learning probabilistic theory helps students understand and deconstruct the problem itself.
Then select and correctly use mathematical models, AI tools, package software, and final result presentation
This course is expected to teach the following content within one semester
1. Experiments, models and probability
2. Random variables (discrete, continuous)
3. Conditional probability and related AI models
Some courses will be paired with python/matlab/excel examples
機率學主要的目的在於介紹和解析機會的結構及其相關之變數與函
數。
這方面的知識為許多進一步研究涉不確定性因素問題的學問的
基礎。本課程引導同學接觸一些有趣的理論和實例。
The main purpose of probability science is to introduce and analyze the structure of chance and its related variables and functions.
Count.
This knowledge provides a basis for further research on issues involving uncertainty factors.
Basics. This course introduces students to some interesting theories and examples.
1. 機率學(Probability and Stochastic Processes) 3th, Roy D. Yates(作), 賴玲瑩(譯), 中文
2. 當代機率：理論與應用 4/e Ghahramani(作), 朱蘊鑛(譯), 中文
1. Probability and Stochastic Processes 3th, Roy D. Yates (author), Lai Lingying (translator), Chinese
2. Contemporary Probability: Theory and Application 4/e Ghahramani (author), Zhu Yunkui (translator), Chinese
| 評分項目 Grading Method | 配分比例 Grading percentage | 說明 Description |
|---|---|---|
| 作業作業 Homework |
40 | |
| 期中期中 Midterm |
30 | |
| 期末期末 End of term |
30 |
