ITM150 Python Programming for Deep Learning / 深度學習與Python實作

Class Schedule: Friday 6(14:10) ~ 8(17:00) / 每周五 14:10~17:00 (第6,7,8節)


1.Exam or Project: 60%
2.Homework and exercise: 30%
3.Regular performance (classroom behavior): 10% (Perfect attendance base score: 4 points)
4. Absence without leave will result in a grade deduction depending on the situation.
未請假缺席視情況扣分
5. Late attendance (more than 15 minutes late) or absence (missing class without leave) will result in a deduction from the total grade, depending on the situation (Perfect attendance does not guarantee a full score for participation).
遲到 (15分鐘以上算遲到)、缺席(未請假缺課): 視情況扣總成績 (全勤平時成績不是滿分)

We have a Teams group for this course, and all announcements will be posted there.
Please install Teams and ensure that you can log in to the school’s Teams group.
我們有Teams群組,課程公告都會發在那邊,請同學先行安裝、確認學校的 Teams群組可以登入。

Lecture PDF Password: cloud

Guidelines for all reports and assignments in this course: (本課程所有報告、作業說明:)
1. Do not use materials with copyright concerns. 
(若資料有著作權疑慮,請勿使用) 2. Only upload reports, source code, and supporting documents to the e-learning platform (no need to upload data).
(僅需上傳報告、程式碼、輔助說明文件到 e-learning (資料不需要上傳)) 3. Downloaded data is to be used exclusively for this course. After completing the report, please destroy or delete the data.
(下載的資料只做本課程使用,完成報告後請銷毀、刪除資料) 4. Do not use code from other courses, projects, or laboratory developments. Open-source code can be used but must be properly cited.
(請勿使用其他非本課程、專題、專案、實驗室開發的程式碼;開源程式碼可使用但須標明出處)
Week# Date Outline
1 02-21 Introduction
2 02-28 Holiday
3 03-07 PyTorch Tensor and practice
4 03-14 Neuron network: ANN, DNN, Activation Function, Loss Function, Backpropagation, Optimizer, tourch.nn
5 03-21 Perceptron
6 03-28 Tensorboard and NN
7 04-04 Holiday
8 04-11 Convolutional Neural Network
9 04-18 TransferLearning
10 04-25 Data Augmentation.
11 05-02 SSD
12 05-09 Unet
13 05-16 Autolabelimg
14 05-23 YOLOv5
15 05-30 Holiday
16 06-06 Project Presentation
17 彈性學習
18 彈性學習

© Chi-Ching's LAB