11120BAI700500 統計與機器學習概論二
Introduction of Statistics and Machine Learning (II)

Instructors: 楊立威、李政霖、羅中泉、劉奕汶、楊自雄
(lwyang@life.nthu.edu.tw; johnli101061255@gmail.com; cclo@mx.nthu.edu.tw;
ywliu@ee.nthu.edu.tw; tyang@mx.nthu.edu.tw )

Date: T234

TA: Chris Ortiz (Christopherllynardortiz@gmail.com)

Introduction to Machine Learning, Fourth Edition, Ethem Alpaydin Course Outline

Section 1
2/20 Introduction to Machine Learning (LW Yang)

2/27 Supervised Learning (CL Li)
3/5 Bayesian Decision Theory/ Parametric Model (CL Li)
3/12 Decision tree / Random Forest (CL Li)
3/19 Random Forest/ Gradient Boost (CL Li)

3/26 Multivariates / Dimension reduction (LW Yang)
4/2 No Class in School Anniversary Celebration /校慶週停課
4/9 Clustering I / Linear Discrimination (LW Yang)

4/16 Dimension Reduction & Feature Selection (CC Lo)

4/23 Support Vector Machine I (YW Liu)
4/30 Support Vector Machine II (YW Liu)
5/7 Single layer Perceptron / Multilayer Perceptron (YW Liu)

5/14 Deep learning (Nick Yang)
5/21 DNN, CNN, RNN (Nick Yang)
5/28 Design Suitable Machine Learning Experiments I (Nick Yang)

6/4 CNN in Real-World Applications: Image Segmentation and object Detection (CC

4 Homework + 1 Homework or quiz (20% each)

AI 使用規則 (Indicate which of the following options you use to manage student use
of the AI) - 有條件開放,請註明如何使用生成式AI於課程產出 Conditionally open; please
specify how generative AI will be used in course output