Implementation of the K-Means Algorithm, Linear Regression, Logistic Regression, Decision Tree Algorithm, Random Forest Algorithm

Customer Segmentation using Kmeans, than used Random Forest for prediction about new customers

Simple kmeans algorithm implementation in java.

Projeto baseado em dataset de notas verdadeiras e falsas para validação através webapp datadriven.

Naive Implementation of Machine Learning Algorithms in distributed frameworks MapReduce and Spark

implements the elbow method to determine the optimal number of clusters (k) for a given dataset using the K-means clustering algorithm.

Repositorio usado para almacenar las prácticas de la asignatura Ingeniería del Conocimiento,

This repository includes usage of KMeans algorithm on MapKit Library

Sample of K-means Clustering

Stock market clustering of companies using K-means algorithm

This repository has some clustering techniques implemented from scratch to understand and grasp basic concepts.

A collection of my practices using the following algorithms: DBSCAN, KNN, Decision Tree Classifier, K-means, Apriori, SMOTE, SVM

This repository contains an introduction to Machine Learning with Python.

Building model using KMeans

대한민국의 인구 밀도에 따른 최적화된 행정구역을 KMeans로 재구성한 프로젝트.

Few simple implementations of common ML algorithms from scratch (numpy)

Implementation of K-means algorithm using Hadoop and Mapper side join.

The implementations in this repository deal with clustering and dimensionality reduction for MNIST digits dataset. Kmeans clustering algorithm is implemented. Also different hierarchical clustering algorithms are tested. We also play with the PCA and TSNE embeddings of the MNIST dataset.

A k-means algorithm implementation to c language.