查詢教學大綱與進度

教學大綱與進度

課程基本資料：

學年期課號課程名稱階段學分時數修教師班級人撤備註

111-2 315973 深度學習 1 3.0 3 ★ 彭朋群
曾恕銘 AI雙聯專班 23 0 應用組，碩一修，5.13 5.28 6.25 3.18 4.9 4.29

學年期	課號	課程名稱	階段	學分	時數	修	教師	班級	人	撤	備註
111-2	315973	深度學習	1	3.0	3	★	彭朋群曾恕銘	AI雙聯專班	23	0	應用組，碩一修，5.13 5.28 6.25 3.18 4.9 4.29

教學大綱與進度：

教師姓名曾恕銘　教師諮商時間(Office Hours)

Email shuming@ntut.edu.tw

最後更新時間 2023-01-05 12:22:01

課程大綱 This course contains labs with source codes and step-by-step instructions. The course adopts problem based lerning, concentrating on the necessary background on these machine learning labs. The content includes introduction and computer tools, DNN with labs, learning methods with labs, CNN with labs, autoencoder with labs, and latest self attention/transformer case study Video Chaptering appliable to Youtube.

課程進度 Week 1: Machine learning introduction and computer tools, Deep Neural Networks (DNN)with Labs Week 2: Learning methods with Labs (AI玩遊戲) Convolutional Neural Network (CNN) with Labs (AI影像分類/物件偵測) Autoencoder with Labs (AI影像去雜訊/著色) Week 3: transformer (AI寫金庸小說/寫學習歷程檔案) with case study scene boundary detection (AI影片分章) Lab report (one group of students reports one lab)

評量方式與標準 Lab report (one group report one lab)

使用教材、參考書目或其他 【遵守智慧財產權觀念，請使用正版教科書，不得使用非法影印教科書】

使用外文原文書：否
References Tan, Steinbach, Karpatne, Kumar, Introduction to Data Mining, 2e, 2019. Mendenhall and Sincich, Statistics for engineering and the sciences, 5/e, Prentice Hall. Zheng Yuxi, A Preliminary Study on Key Technologies of Artificial Intelligence, 2019.8.26 Jinwoo Shin, Deep Learning for Optimization, Communication and Networks, The East Asian School of Information Theory & Communication (EASITC), August 6-10, 2018 https://www-users.cs.umn.edu/~kumar001/dmbook/index.php#item4 http://www.willamette.edu/~gorr/classes/cs449/intro.html https://speech.ee.ntu.edu.tw/~hylee/ml/2021-spring.html http://www.aiotlab.org/teaching/dl_app.html NVIDIA DLI Deep Learning Basic Theory and Practice Microsoft Azure Service Custom Vision Cavedu Education Team Generate Network_Zeng Jihong 02_Auto Encoder Zhai, Xiaohua, et al. "S4l: Self-supervised semi-supervised learning." Proceedings of the IEEE/CVF International Conference on Computer Vision. 2019.

課程諮詢管道 office hours or by email

備註
If the distance class becomes necessary, all lectures, exam, oral reports will be held via Microsoft Teams. We will have roll calls and you may be required to turn on the camera and mic in the class.

教師姓名	曾恕銘　教師諮商時間(Office Hours)
Email	shuming@ntut.edu.tw
最後更新時間	2023-01-05 12:22:01
課程大綱	This course contains labs with source codes and step-by-step instructions. The course adopts problem based lerning, concentrating on the necessary background on these machine learning labs. The content includes introduction and computer tools, DNN with labs, learning methods with labs, CNN with labs, autoencoder with labs, and latest self attention/transformer case study Video Chaptering appliable to Youtube.
課程進度	Week 1: Machine learning introduction and computer tools, Deep Neural Networks (DNN)with Labs Week 2: Learning methods with Labs (AI玩遊戲) Convolutional Neural Network (CNN) with Labs (AI影像分類/物件偵測) Autoencoder with Labs (AI影像去雜訊/著色) Week 3: transformer (AI寫金庸小說/寫學習歷程檔案) with case study scene boundary detection (AI影片分章) Lab report (one group of students reports one lab)
評量方式與標準	Lab report (one group report one lab)
使用教材、參考書目或其他	【遵守智慧財產權觀念，請使用正版教科書，不得使用非法影印教科書】使用外文原文書：否 References Tan, Steinbach, Karpatne, Kumar, Introduction to Data Mining, 2e, 2019. Mendenhall and Sincich, Statistics for engineering and the sciences, 5/e, Prentice Hall. Zheng Yuxi, A Preliminary Study on Key Technologies of Artificial Intelligence, 2019.8.26 Jinwoo Shin, Deep Learning for Optimization, Communication and Networks, The East Asian School of Information Theory & Communication (EASITC), August 6-10, 2018 https://www-users.cs.umn.edu/~kumar001/dmbook/index.php#item4 http://www.willamette.edu/~gorr/classes/cs449/intro.html https://speech.ee.ntu.edu.tw/~hylee/ml/2021-spring.html http://www.aiotlab.org/teaching/dl_app.html NVIDIA DLI Deep Learning Basic Theory and Practice Microsoft Azure Service Custom Vision Cavedu Education Team Generate Network_Zeng Jihong 02_Auto Encoder Zhai, Xiaohua, et al. "S4l: Self-supervised semi-supervised learning." Proceedings of the IEEE/CVF International Conference on Computer Vision. 2019.
課程諮詢管道	office hours or by email
備註	If the distance class becomes necessary, all lectures, exam, oral reports will be held via Microsoft Teams. We will have roll calls and you may be required to turn on the camera and mic in the class.