K-Means algorithm parallelized in CUDA
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Updated
Sep 5, 2024 - Cuda
K-Means algorithm parallelized in CUDA
This repository aims to provide an overview of various clustering methods, along with practical examples and implementations.
An API for managing chat completions, fine-tuning, payments, plans, and configurations.
Turn your best memories into plotter art
In this Python notebook, we explore how K-Means can be used for customer segmentation to gain a competitive advantage and improve a business's bottom line.
This program implements the K-means clustering algorithm using OpenMP APIs. The K-means algorithm is a popular method of vector quantization that aims to partition n observations into k clusters. Each observation is assigned to the cluster with the nearest mean, serving as a prototype of the cluster.
This Machine Learning repository encompasses theory, hands-on labs, and two projects. Project 1 analyzes customer segmentation for marketing using clustering, while Project 2 applies supervised classification in marketing and sales.
Customer Segmentation using R
This repo contains the Implementation of K-Means Clustering Algorithm from scratch and an Image Segmentation Project, implemented using the same algorithm.
A pipe-friendly command-line tool for k-means clustering and neighbor analysis. Built around Unix principles: read from stdin, write to stdout, and stay composable. Ideal for shell pipelines, data exploration, and automation on macOS and Linux.
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...
K-means clustering algorithm using MapReduce.
A C implementation of K-Means clustering algorithm with Python bindings
The K -Means algorithm implementation from scratch in Python based on Euclidean distance
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.
A movie recommendation engine built with python and a Qt GUI.
Parallel-K-Means-Algorithm
Unsupervised learning algorithms are used here. agglomerative algorithms and k-means clustering are used here.
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