This repository contains the code and report for the TU Berlin's Machine
Learning Lab Course assignments from Klaus-Robert Müller. 


Assignment 1:
The assignment involves the study, implementation and application of algorithms
for dimension reduction (PCA, LLE), evaluation (AUC) and outlier detection (Gamma
idx, Kappa idx and others). 

Assignment 2:
The assignment involves the study, implementation and application of algorithms
for clustering algorithms. In particular, k-Means, Gaussian MixtureModels, 
Agglomorative Clustering are investigated.

Assignment 3:
The assignment involves the study, implementation and application of algorithms
for cross validation and kernel ridge regression. These classes are then used to
reproduce the results of a research paper and investigate 5 different
classification datasets.

Assignment 4: 
This assignment focused on SVMs and neural networks. It required the implementation of each,
and the application to various small datasets.