Kmeans, Kmeans++, Gaussian Mixtures

A collection of the assignments in the course advanced machine learning

Code for the paper "Reconstructuring Sparse Multiplex Networks With Application to Covert Networks"

Machine Translation lab Implementation

Manual Implementation of some machine learning algorithms

Find Clusters of data using Expectation Maximization algorithm on mixture of gaussians

Homework Code for UCLA STATS 115 (Probabilistic Decision Making) Fall 22 Offering

This repository is for the ICML'24 paper: "Unveiling the Cycloid Trajectory of EM Iterations in Mixed Linear Regression"

This is an approach towards reproducing the stauffer-grimson background Subtraction Paper, "Adaptive background mixture models for real-time tracking" published in 1999. A recreation of stauffer grimson background subtraction. One of the earliest and pioneering works that led to modern Computer Vision.

Modeling correlated count data

Implementation of Task-Parameterized-Gaussian-Mixture-Models as presented from S. Calinon in his paper: "A Tutorial on Task-Parameterized Movement Learning and Retrieval"

Solving NQueen and HeavyNqueen, Hill Climbing and Astar, based on Python, EM for Clustering

This repository contains different implementations of ML algorithms from scratch.

implementing k-means, GMMs from scratch

OpenCV Machine Learning samples

Spring 2021 Machine Learning (CS 181) Homework 5

Application of unsupervised learning and dimensionality reduction towards multiple problem sets.