Caveat: This repository is not updated anymore.
This repository provides python examples for better understanding of some fundamental machine learning tools. Currently it includes the following topics:
- Dimensionality Reduction (PCA, MDS, Isomap, Diffusion Maps)
- Fihser's Linear Discriminant Analysis and Maximum Likelihood Discriminant Analysis
- K-means clustering
- Support Vector Machines (primal and dual problems, Kernel based methods)
These codes are supplementary materials for the lecture Fundamentals of Big Data Analytics.