STAT3612 Data Mining (Statistical Machine Learning)

HKU 2018-19 Semester 2

Course Syllabus: PDF

Instructor: Dr. Aijun Zhang (ajzhang at hku dot hk; RR224)
Tutor: Dr. Gilbert Lui (csglui at hku dot hk; RR118)
Lecture Hours:
Monday 5:30pm — 6:20pm (T3)
Thursday 4:30pm — 6:20pm (T3)
Tutorial Hours:
Monday 4:30pm — 5:20pm (RR101)
Tuesday 9:30am — 10:20am (RR101)

Moodle@HKU: http://moodle.hku.hk/

Class Schedule Lecture Notes Supplementary Tutorial Notes
Lecture 1: Jan 14-17 Introduction to DS, ML, AI (Slides)
Big Data, Data Science Venn Diagram,
Machine Learning, Artificial Intelligence
Lecture1.ipynb
Lecture 2: Jan 21-24 Data Exploration (Slides)
Exploratory Data Analysis
Data Visualization, Data Manipulation
Lecture2.ipynb Tutorial1.ipynb
Lecture 3: Jan 28-31 Linear Regression
LM, LSE, Model Inference
Diagnostics, Variable Selection
Lecture 4: Feb 14 Basis Expansion
Feature Engineering,
Nonparametric Regression, GAM
Lecture 5: Feb 18-21 Regularization
Smoothing spline, Piecewise smoothness,
Ridge Regression, Lasso, Sparse Modeling
Lecture 6: Feb 25-28 Classification
Logistic/Softmax regression
LDA/QDA, kNN, Confusion matrix, ROC curve
Lecture 7: March 11-14 Stochastic Optimization
First-order method,
Large-scale logistic modeling
Lecture 8: March 18-21 Tree-based Methods
Classification and Regression Trees
Bagging, Random Forest, GBM
Lecture 9: March 25-28 Support Vector Machines
Separating Hyperplane, Kernel method,
Hyperparameter optimization, AutoML
Lecture 10: April 1-4 Neural Networks
MLP, Backpropagation algorithm, Deep Learning
Lecture 11: April 8-11 Interpretable Machine Learning
Explainable Neural Networks, SOSxNN
Lecture 12: April 15-18 Unsupervised Learning
K-means, PCA, t-SNE
Apr 25 Group Project Presentation