| Relevance of Course Objectives and Core Learning Outcomes(%) |
Teaching and Assessment Methods for Course Objectives |
| Course Objectives |
Competency Indicators |
Ratio(%) |
Teaching Methods |
Assessment Methods |
| 讓學生熟悉PyTorch與TensorFlow基礎知識、迴歸、前饋神經網路、卷積神經網路、遞歸神經網路、自編碼模型、生成對抗網路、Seq2seq 自然語言處理、遷移學習等深度學習的基礎知識與實作 |
| 1.Professional Knowledge and Practical Application |
| 2.Independent Problem-Solving |
| 3.Creative Thinking |
|
|
| Lecturing |
| Exercises |
| topic Discussion / Production |
|
|
| Course Content and Homework/Schedule/Tests Schedule |
| Week |
Course Content |
| Week 1 |
課程簡介 (實體授課) |
| Week 2 |
PyTorch基礎知識 (採非同步遠距教學) |
| Week 3 |
實作問題討論 (實體授課) |
| Week 4 |
迴歸(Torch) (採非同步遠距教學) |
| Week 5 |
實作問題討論 (實體授課) |
| Week 6 |
前饋神經網路(Torch) (採非同步遠距教學) |
| Week 7 |
實作問題討論 (實體授課) |
| Week 8 |
卷積神經網路(Torch) (採非同步遠距教學) |
| Week 9 |
實作問題討論 (實體授課) |
| Week 10 |
遞歸神經網路(Torch) (採非同步遠距教學) |
| Week 11 |
實作問題討論 (實體授課) |
| Week 12 |
自編碼模型(Torch) (採非同步遠距教學） |
| Week 13 |
實作問題討論 (實體授課) |
| Week 14 |
生成對抗網路(Torch) (採非同步遠距教學) |
| Week 15 |
實作問題討論 (實體授課) |
| Week 16 |
遷移學習(Torch) (採非同步遠距教學)
|
self-directed
learning |
02.Viewing multimedia materials related to industry and academia.
|
|
| Evaluation |
| 作業 100% |
| Textbook & other References |
| 自訂教材 |
| Teaching Aids & Teacher's Website |
| ilearning |
| Office Hours |
| 週五 14:00 ~ 16:00 |