課程名稱 |
神經網路 Neural Networks |
開課學期 |
109-2 |
授課對象 |
醫學院 腦與心智科學研究所 |
授課教師 |
吳恩賜 |
課號 |
GIBMS7015 |
課程識別碼 |
454EM0390 |
班次 |
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學分 |
3.0 |
全/半年 |
半年 |
必/選修 |
選修 |
上課時間 |
星期五6,7,8(13:20~16:20) |
上課地點 |
基1203 |
備註 |
本課程以英語授課。 限碩士班以上 且 限本系所學生(含輔系、雙修生) 總人數上限:15人 |
Ceiba 課程網頁 |
http://ceiba.ntu.edu.tw/1092GIBMS7015_ |
課程簡介影片 |
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核心能力關聯 |
核心能力與課程規劃關聯圖 |
課程大綱
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課程概述 |
This course will introduce basic principles of neural networks in relation to human cognition with applied practical programming of simple neural networks. Students will read three modeling papers and apply the neural network models in these papers to create their own neural networks. Three examples of networks will be covered: 1) Attractors (Hopfield, 1982), 2) Backpropagation (Perceptron; Rumelhart et al., 1986), 3) Unsupervised Learning (Von Der Malsburg, 1973). |
課程目標 |
Program the above three neural networks using any of the above software languages and apply the neural networks to real-life problems or simulations of human cognition. |
課程要求 |
Students in Graduate Institute of Brain and Mind Sciences; excellent confidence in computer programming in either R, Matlab, or Python; maximum 10 students; no auditing; your own computer with above softwares installed and ready to go. |
預期每週課後學習時數 |
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Office Hours |
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指定閱讀 |
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參考書目 |
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評量方式 (僅供參考) |
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週次 |
日期 |
單元主題 |
Week 1 |
2/26 |
Introduction: Why model? And linear algebra. (Jordan, 1986) |
Week 2 |
3/05 |
Perceptrons: Nomenclature & general framework (Aggarwal, 2018, Ch. 1) |
Week 3 |
3/12 |
Hopfield networks: Introduction (Hopfield, 1982) |
Week 4 |
3/19 |
Hopfield networks: Make your own autoencoder |
Week 5 |
3/26 |
Hopfield networks: Apply and describe your autoencoder system |
Week 6 |
4/02 |
No Class (Tomb-Sweeping Festival) |
Week 7 |
4/09 |
Backpropagation (Rumelhart, 1986) |
Week 8 |
4/16 |
Backpropagation (Assignment 2 on Autoencoders due) |
Week 9 |
4/23 |
Backpropagation |
Week 10 |
4/30 |
Backpropagation |
Week 11 |
5/07 |
Unsupervised Learning (Von der Malsburg, 1973) |
Week 12 |
5/14 |
Unsupervised Learning (Assignment 3 on Backprop due) |
Week 13 |
5/21 |
Unsupervised Learning |
Week 14 |
5/28 |
Unsupervised Learning |
Week 15 |
6/04 |
TBA |
Week 16 |
6/11 |
TBA, Assignment 4 on U-Learning due
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Week 17 |
6/18 |
TBA |
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