Implementation of k-means algorithm in C (standard C89/C90
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Updated
Sep 15, 2024 - C
Implementation of k-means algorithm in C (standard C89/C90
K-means clustering algorithm using MapReduce.
K-Means algorithm parallelized in CUDA
A K-Means algorithm implementation involving various optimization techniques. Used to group MNIST dataset of hand-written numbers 0-9.
Customer Segmentation using R
This repository contains an example of using K-means clustering to partition data into distinct groups based on similarity.
Predict Alaska's Salmon population using various Machine Learning models
An implementation of k-means algorithm in Zig
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.
A C implementation of K-Means clustering algorithm with Python bindings
Cluster Visualization Tool
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.
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.
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.
The K -Means algorithm implementation from scratch in Python based on Euclidean distance
An API for managing chat completions, fine-tuning, payments, plans, and configurations.
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.
An analysis using unsupervised Machine Learning algorithm to discover unknown patterns
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