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課程名稱 |
深度學習之應用
Applied Deep Learning |
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開課學期 |
106-1 |
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授課對象 |
電機資訊學院 資訊網路與多媒體研究所 |
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授課教師 |
陳縕儂 |
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課號 |
CSIE5431 |
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課程識別碼 |
922 U4340 |
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班次 |
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學分 |
3.0 |
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全/半年 |
半年 |
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必/選修 |
選修 |
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上課時間 |
星期一7,8,9(14:20~17:20) |
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上課地點 |
資101 |
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備註 |
初選不開放。
限電資學院學生(含輔系、雙修生)
總人數上限：80人 |
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課程網頁 |
https://www.csie.ntu.edu.tw/~yvchen/f106-adl/ |
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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 |
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課程大綱
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為確保您我的權利,請尊重智慧財產權及不得非法影印
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課程概述 |
Learning the basic theory of deep learning and how to apply to various applications |
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課程目標 |
The students are expected to understand
1) how deep learning works
2) how to frame tasks into deep learning problems
3) how to use deep learning toolkits to implement the designed models, and
4) when and why specific deep learning techniques work for specific problems. |
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課程要求 |
Proficiency in Python
College Calculus
Linear Algebra
Probability
Machine Learning (preferred but optional)
Statistics (preferred but optional) |
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預期每週課後學習時數 |
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Office Hours |
另約時間 |
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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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No. |
項目 |
百分比 |
說明 |
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1. |
Project |
30% |
Dialogue State Tracking Challenge/Machine Comprehension |
2. |
Assignment 5 |
15% |
Game Playing |
3. |
Assignment 4 |
15% |
Language Generation |
4. |
Assignment 3 |
15% |
Language Understanding |
5. |
Assignment 2 |
15% |
Sentiment Analysis |
6. |
Assignment 1 |
15% |
Word Embedding |
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