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

高等演算法

Advanced Algorithm

學期
114-2
學分
3 學分
當期課號
440102
永久課號
BTBI30115
開課單位
生物資訊及系統生物研究所
授課教師
中研院國際學程
類別
必修
上課時間表
週五
6
14:20–15:10
高等演算法
3 節連堂
7
15:30–16:20
8
16:30–17:20

* 根據陽明交大上課時間表所列

概述

This course is basically about data mining, machine learning and statistical modeling from data, and some other algorithms and applications. There are 7 topics given in the way of Videos Preview (about 2~3 hours) + In-class discussions (about 1~1.5 hours). Below please find the link that WILL provide the links of the following: (1) the videos to be watched BEFORE the class (2) the questions to be discussed IN the class (3) the homework to be completed AFTER the class (https://reurl.cc/eGWkoL)

先修科目

The course details may change (time, location, topic, etc.), please refer to the class syllabus on the TIGP Bioinformatics Program before each class: https://idv.sinica.edu.tw/tigpbio/index.html 【For Non-BP student】 For Non-BP student to register/sit-in any BP course, it is required to gain course chair's permission: (1) Basic Enrollment Information form (https://forms.gle/oK7vJzzrx9EvybbT9) (2) TIGP-BP Course Registration Consent Form (https://idv.sinica.edu.tw/tigpbio/index/TIGP%20Bioinformatics_Class%20Registration%20Consent%20Form.docx) ※ Deadline: the 4th week of each semester. ※ Signature of the course chair should be collected before submission. Incomplete form will not be accepted. ※Course grade will NOT be given (even class enrollment is completed at school) if fail to follow the above procedures.

週次計畫
週次主題
第 1 週
第 2 週
第 3 週
第 4 週
第 5 週
第 6 週
第 7 週
第 8 週
第 9 週
第 10 週
第 11 週
第 12 週
第 13 週
第 14 週
第 15 週
第 16 週
教科書

Reserved in the library of the Institute of Information Science: 1. Learning from Data- A Short Course (Abu-Mostafa, Magdon-Ismail, Lin, 2012) 2. Learning Pattern Classification (Duda, Harg, and Stork, 2001) 3. An Introduction to Support Vector Machines and Other Kernel-based Learning Methods (Cristianini and Shawe-Taylor, 2000) 4. [DL in Life Science] https://mit6874.github.io/ 5. [ML for Genomics] https://www.classcentral.com/course/youtube-6-047-6-878-machine-learning-for-genomics-fall-2020-48203