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

Simple kmeans algorithm implementation in java.

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

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

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

KMeans algorithm implementation.

Arsip Data Loket Bus With KMeans - PHP Codeigniter

Dating App

In this project, I use K-means as an unsupervised learning algorithm to perform customer clustering to identify better strategies based on RFM model

KMeans Implementation in Python

Classifying iris and fashion-mnist datasets using different algorithms.

News feed aggregator using k-means clustering

clustering tweets using Jaccard distance metric and K-means clustering algorithm.

Machine Learning Algorithms(Kmeans,Kmedoids,KNN and Naive bayes) with data cleaning and visualization

Udemy course recomendation engine

Predicting user behaviour in a music streaming platform, NetEase Cloud Music (NCM), using machine learning and data analysis

KMeans Clustering of data using Sklearn library, numpy and Pickle data

Lead Scoring Analysis and Segmentation. A lead scoring analysis is conducted for an online teaching company with a low client conversion rate. The goals are to reverse this trend by using a machine learning model based on available company data and to categorize customers with an effective segmentation.

iris and kdd cup 1999 classification