Analysis and Implementation on Machine Learning Models and Methods for HKU Course COMP3314 by Dr. Li-Yi Wei.
The Exercises include rigurous analysis of certain machine learning models, as well as implementation of them in python (sklearn and keras). View Here for a user-friendly revision of the course and my work. The original course pages are from 1iyiwei/pyml.
1 Warmup.ipynb
: Sorting and Line fitting
2 Perceptron and SGD.ipynb
: Linear perceptron and SGD
3 Kernel, Bayes and Models.ipynb
: RBF kernel, Kernel SVM Complexity, Gaussian Bayes, and Basic Classifiers
4 Data Processing.ipynb
: Sequential feature selection and PCA versus LDA
5 Training and Ensemble.ipynb
: K-fold validation, Precision-recall curve, and Ensemble learning
6 Cluster and CNN.ipynb
: Clustering for Digits and CNN on Cifar-10 (We use Wide ResNet and acheieved 94%)