Material for the Pattern Recognition course FYS-3012 at UiT The Arctic University of Norway
Contains code involving CS 503 - Lab 3 : Implementation of Support vector Machine.
Support Vector Machines (SVMs) from scratch, without dedicated packages, for the classification of linear and non-linear data.
Predict probability of default on credit
This project implements back propagation algorithm of neural networks. It handles binary classification on various real world dataset. It is implemented in java.
A supervised machine learning model that classifies environmental sounds (such as rain, thunder etc.) using Support Vector Machines and kernel-based feature transformations. Instead of using DNNs, this project leverages audio feature extraction (MFCCs, spectral features, chroma) and SVM’s mathematical rigor to recognize sound classes
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