本課程的目的是讓學生了解前饋式與遞迴式神經網路設計原理，及其在計算科學、監督式學習系統、非監督式學習系統與最佳化領域的應用。
The purpose of this course is to enable students to understand the principles of feedforward neural network design, recurrent neural network design, and its applications to computing science, supervised learning systems, unsupervised learning systems, and optimization.
先修科目Prerequisites
無
None
教學方式Teaching Methods
講課
Lecturing
學生課後書面報告
After class written report
小組討論
Group discussion
學生上台報告
Oral presentation
評量方式Assessment
期中報告
Midterm report
期末報告
Final report
專題報告
Project report
個人上台報告
Oral Report
出席狀況
Class attendance
參考書目Reference
1. Simon O. Haykin, Neural Networks and Learning Machines, Prentice Hall, 3rd edition, 2008 (ISBN-13: 978-0131471399).
2. Satish Kumar, Neural Networks: A Classroom Approach, McGraw Hill Education, 2nd edition, 2012 (ISBN-13: 978-1259006166).