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
112-2	328170	深度學習	1	3.0	3	★	姚立德	電機所 電資外生所 智慧鐵道學位學程 人工智慧學位學程 創新AI學位學程	49	5	電機所、電資AI、創新AI、電資外生所和智慧鐵道班合開

教學大綱與進度：

教師姓名	姚立德　教師諮商時間(Office Hours)
Email	ltyao@ntut.edu.tw
最後更新時間	2024-05-27 11:06:59
課程大綱	1. Introduction to Neural Networks 2. Shallow Neural Networks 3. Training Deep Neural Networks 4. Teaching Deep Learners to Generalize 5. Recurrent Neural Networks 6. Long Short-term Memory Neural Networks 7. Convolutional Neural Networks 8. Deep Reinforcement Learning
課程進度	1. Introduction to Neural Networks (1 wk) 2. Shallow Neural Networks (2 wks) 3. Training Deep Neural Networks (2 wks) 4. Teaching Deep Learners to Generalize (3 wks) 5. Recurrent Neural Networks (2 wks) 6. Long Short-term Memory Neural Networks (2 wks) 7. Convolutional Neural Networks (3 wks) 8. Deep Reinforcement Learning (3 wks)
評量方式與標準	Three take-home exams. (30%, 35%, 35%)
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：是 Neural Networks and Deep Learning, Charu C. Aggarwal, Springer, 2018.
課程諮詢管道	You are welcome to email me with the following email address: ltyao@ntut.edu.tw
課程對應SDGs指標
備註	SDG 4 and 8. After final exam, you are required to learn Deep Reinforcement Learning by reading the tutorial provided in the i-school. Moreover, the second part of final take-home exam. will be conducted from June 9th to 17th. Please carefully read the provided tutorial and watch the uploaded recorded video in i-school.