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
110-2	297774	深度學習	1	3.0	3	★	姚立德	電機所 電資外生所	33	2	◎電機所和電資外生所合開

教學大綱與進度：

教師姓名	姚立德
Email	ltyao@ntut.edu.tw
最後更新時間	2022-03-29 22:55:24
課程大綱	In this course, both the theoretical background and programming techniques of deep learning are introduced. Different neural network structures for deep learning including feedforward neural networks, recurrent neural networks, convolutional neural networks, deep reinforcement learning neural networks, and their applications are introduced. Structure design, parametric tuning, and generalization capability of deep learning are also investigated.
課程進度	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
評量方式與標準	1st project: 30% 2nd project: 30% 3rd project: 40%
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, Springer, 2018. Authour: Charu C. Aggarwal
課程諮詢管道
備註	The class will be changed to an on-line class due to the need for epidemic prevention. Google Meet will be used for the on-line class. The time for on-line class is the same as one for regular classes.