bobub/ml_lab_course
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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.
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