人工智慧正在改變不同行業，深度學習是近期人工智慧討論度最高的知識領域，本課程將透過機器學習的概念切入，了解過往資料分析探勘上的概念，統計概念、迴歸分析、機器學習、類神經網路等，再接續這樣的基礎概念導入深度學習理論，並透過不同應用案例了解深度學習方法的優勢與瓶頸。本課程將以Python程式語言作為課程的案例學習的程式語言，因此，學生必須具備簡單的程式語言基礎。Artificial intelligence is changing to different industries. In-depth learning is the most discussed knowledge area in recent artificial intelligence. This course will enter the concept of machine learning to understand the concepts in past data analysis and exploration, statistical concepts, epistem analysis, machine learning, and neural networks, etc., and then continue this basic concept to guide in in-depth learning theory, and understand the advantages and bottlenecks of deep learning methods through different application cases. This course will use Python programming language as the course's case study, so students must have a simple programming language foundation.
Deep Learning
作者: Ian Goodfellow, Yoshua Bengio, Aaron Courville
出版社: The MIT Press
出版年: 2016
Deep Learning
Author: Ian Goodfellow, Yoshua Bengio, Aaron Courville
Publisher: The MIT Press
Year of publication: 2016
| 評分項目 Grading Method | 配分比例 Grading percentage | 說明 Description |
|---|---|---|
| 作業作業 Action |
40 | |
| 期末專題期末專題 Final topics |
40 | |
| 課堂報告課堂報告 Class Report |
20 |
