機器學習概論
Introduction to Machine Learning
| 節 | 週一 |
|---|---|
A 18:30–19:20 | 機器學習概論 TB435 3 節連堂 |
B 19:30–20:20 | |
C 20:30–21:20 |
* 根據陽明交大上課時間表所列
本課程將介紹許多基本機器學習技術應用在資料分析與預測模型建立。學生也可在這門課學習到如何使用Python搭配NumPy與PyTorch 設計出高效率的大數據運算程式。本課程的主題包括數值資料分析、數學建模、人工神經網路和深度學習。本課程為Python程式設計的進階課程,並沒有包含介紹Python基礎語法與指令。 本課程每週都會有程式設計的作業,總共會有約12次的作業。本課程最後有期末專案,學生組隊完成,每隊1-3人。利用課堂所介紹的機器學習模型套用在自行收集的資料集,完成某種事件的預測。 This course introduces essential machine learning techniques for data analysis and predictive modeling. Students will also learn how to use Python with NumPy and PyTorch to efficiently perform large-scale numerical computations. Topics include numerical data analysis, mathematical modeling, artificial neural networks, and deep learning. As this is an advanced Python programming course, basic Python syntax and instructions will not be covered.
Python programming
Homework: 60% Final project: 40%
| 週次 | 主題 |
|---|---|
| 第 1 週 | Introduction to data analysis and machine learning |
| 第 2 週 | Python Data Structures: Lists, tuples, sets, dictionaries |
| 第 3 週 | Numerical computing with NumPy: Arrays and reduce functions |
| 第 4 週 | Numerical computing with NumPy: Arrays and arithmetic operators |
| 第 5 週 | Numerical computing with NumPy: Linear algebra |
| 第 6 週 | Numerical computing with NumPy: Array manipulation routines |
| 第 7 週 | Machine Learning: KNN & PCA |
| 第 8 週 | Machine Learning: Regression models |
| 第 9 週 | Machine Learning: Data classifiers |
| 第 10 週 | Machine Learning: SVM |
| 第 11 週 | Machine Learning: Artificial neural networks |
| 第 12 週 | Machine Learning: Convolutional neural networks |
| 第 13 週 | Machine Learning: Convolutional neural networks |
| 第 14 週 | Machine Learning: Transformers |
| 第 15 週 | Case study and final project presentation |
| 第 16 週 | Case study and final project presentation |
1. Claus Führer, Jan Erik Solem, and Olivier Verdier, "Scientific Computing with Python: High-performance scientific computing with NumPy, SciPy, and pandas, 2nd Edition," Packt Publishing, July 23, 2021. 2. John D. Kelleher, Brian Mac Namee and Aoife D'Arcy, "Fundamentals of Machine Learning for Predictive Data Analytics," 2nd, MIT Press, 2020. 3. Aurélien Géron, "Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems," 2nd, O'Reilly Media, 2019.
- 地點
- Online meeting
- 時間
- By appointment
- 聯絡方式
- jameschengcs@nycu.edu.tw