11120BAI700500 統計與機器學習概論二 
<br>Introduction of Statistics and Machine Learning (II)
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<br>Instructors: 楊立威、李政霖、羅中泉、劉奕汶、楊自雄 ( lwyang@life.nthu.edu.tw )
<br>Date: T234
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<br>TA: Wendy (Yun-Pei) Chang: mandy29402000tw@yahoo.com.tw  
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<br>Textbook: 
<br>Introduction to Machine Learning, Fourth Edition, Ethem Alpaydin Course Outline
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<br>Section 1
<br>2/14 Introduction to Machine Learning (LW Yang)
<br>2/21 Supervised Learning (CL Li)
<br>2/28 National Holiday
<br>3/7 Bayesian Decision Theory/ Parametric Model (CL Li)
<br>3/14 Decision tree / Random Forest (CL Li)
<br>3/21 Random Forest/ Gradient Boost (CL Li)
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<br>3/28 Multivariates / Dimension reduction (LW Yang)
<br>4/4 No Class in School Anniversary Celebration /校慶週停課
<br>4/11 Clustering I / Linear Discrimination (LW Yang)
<br>4/18 Clustering II with Dimension Reduction (CC Lo)
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<br>4/25 Support Vector Machine I (YW Liu)
<br>5/2 Support Vector Machine II (YW Liu)
<br>5/9 Single la<x>yer Perceptron / Multil<x>ayer Perceptron (YW Liu)
<br>5/16 Deep learning (Nick Yang)
<br>5/23 DNN, CNN, RNN (Nick Yang)
<br>5/30 Design Suitable Machine Learning Experiments I (Nick Yang)
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<br>6/6 (Extra) Design Suitable Machine Learning Experiments II (CC Lo)
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<br>Grading:
<br>4 Homework + 1 Homework or quiz (20% each)?
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