K-means algorithm is implemented from scratch for clustering on iris dataset and MNIST dataset.

In this project, I used unsupervised machine learning techniques to analyze cryptocurrency data.

Parallel-K-Means-Algorithm

A movie recommendation engine built with python and a Qt GUI.

An analysis using unsupervised Machine Learning algorithm to discover unknown patterns

This repository contains an example of using K-means clustering to partition data into distinct groups based on similarity.

The K -Means algorithm implementation from scratch in Python based on Euclidean distance

Cluster Visualization Tool

Unsupervised learning algorithms are used here. agglomerative algorithms and k-means clustering are used here.

We calculate how a country should shift from alert to a warning condition using Action-Rules. This focus also emphasizes the importance of each dataset attribute in generating the country's fragile state index.

Implementation of k-means algorithm in C (standard C89/C90)

Implementation of k-means algorithm in Zig

Predict Alaska's Salmon population using various Machine Learning models

A K-Means algorithm implementation involving various optimization techniques. Used to group MNIST dataset of hand-written numbers 0-9.

In this two cluster approaches are used: hierarchical clustering and K-means clustering. It is unsupervised learning technique for grouping related data points which shows same behaviour in the dataset regardless of the outcome.

Customer Segmentation using R

A C implementation of K-Means clustering algorithm with Python bindings

This Repo contains various Machine learning Algorithm including Linear regression, Logistic regression, Neural Networks, SVM, Clustering algorithms, K-means Algorithm, Anomaly detection, and Recommander system etc...