STAT3612 Data Mining (Statistical Machine Learning)
HKU 201819 Semester 2
Course Syllabus: PDF
Instructor: Dr. Aijun Zhang (ajzhang at hku dot hk; RR224) Moodle@HKU: http://moodle.hku.hk/ 
Class Schedule  Lecture Notes  Supplementary  Tutorial Notes 
Lecture 1: Jan 1417  Introduction to DS, ML, AI (Slides) Big Data, Data Science Venn Diagram, Machine Learning, Artificial Intelligence 
Lecture1.ipynb  
Lecture 2: Jan 2124 
Data Exploration (Slides) Exploratory Data Analysis Data Visualization, Data Manipulation 
Lecture2.ipynb  Tutorial1A.ipynb 
Lecture 3: Jan 28Feb 14 
Generalized Linear Models (Slides) Linear Regression, Logistic Regression Multinomial Logit, CoxPH model 
Lecture3.ipynb  Tutorial1B.ipynb 
Lecture 4: Feb 1821 
Basis Expansion (Slides) Feature Engineering, Nonparametric Regression 
Lecture4.ipynb  Tutorial2A.ipynb 
Lecture 5: Feb 2528 
Structural Regularization I (Slides) Regularized generalized linear models Ridge Regression, Lasso, Sparse Modeling 
Homework 1: Due 12/3  Tutorial2B.ipynb 
Lecture 6: March 1114 
Structural Regularization II (Slides) Nonparametric regression Smoothing spline, Piecewise smoothness 
Lecture6Rnb.html Project Proposal: Due 27/3 

Lecture 7: March 1821 
Stochastic Optimization Firstorder method, GD Demo Largescale logistic modeling 
Lecture7.html Test 1: 18/3 (Monday) Past papers: a, b 
Tutorial3.ipynb 
Lecture 8: March 2528 
Treebased Methods (HTML) Classification and Regression Trees Bagging, Random Forest, GBM 
TalkCN.pdf  Tutorial4.ipynb 
Lecture 9: April 1 
Support Vector Machines Separating Hyperplane, Kernel method, Hyperparameter optimization, AutoML 

Lecture 10: April 48 
Neural Networks MLP, Backpropagation algorithm, Deep Learning 

Lecture 11: April 11 
Interpretable Machine Learning Explainable Neural Networks, SOSxNN 

Lecture 12: April 1518 
Unsupervised Learning Kmeans, PCA, tSNE 

Apr 25  Group Project Presentation 