Course Syllabus

Course Information：

Year-Semester	Course Number	Course Name	Phase	Credits	Hours	Required/Elective	Instructor	Class	Student NO.	Withdraw	Note
Spring Semester Year 2023	313512	Deep Learning	1	3.0	3	★	YAO LEEHTER	GEE IEECSG GEECS MSAI	63	0	電機所、電資外生所和AI學程合開

Course Plan：

Instructor	YAO LEEHTER　Office Hours
Email	ltyao@ntut.edu.tw
Last Updated	2022-12-21 11:45:07
Course Objective	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.
Course Schedule	1. Introduction to Neural Networks 2. Shallow Neural Networks 3. Deep Neural Networks 4. Recurrent Neural Networks 5. Long Short-term Memory Neural Networks 6. Convolutional Neural Networks 7. Deep Reinforcement Learning
Evaluation and grading policy	3 take-home exams.
Materials	All right reserved. Do not reproduce without permission. Foreign-language textbooks:Yes Text Book: Neural Networks and Deep Learning, Springer, 2018. Authour: Charu C. Aggarwal
The access to curricular consultation	Office hours
The course corresponds to the SDGs
Note	Microsoft Teams