Extensive EDA providing detailed analysis of penguin dataset; ML models built to predicate penguin features for superior penguin management

Stylometry & Machine Learning: Authorship Attribution.

KMeans Clustering using Spark on Uber's ride share data - Case Study (Big Data Analytics @uber)

A simple static site using WASM to quickly quantize image colors with K-Means++

Performing customer segmentation using KMeans clustering algorithm

Data Science Assessment from NielsenIQ

This repository shows a use case of Graph ML for casinos in marketing: Market Segmentation . Skills: Azure SDK, azure datalake, node2vec, graphml, geometric pytorch, gnn

The dataset includes the following columns: Id, SepalLengthCm, SepalWidthCm, PetalLengthCm, PetalWidthCm, and Species. We will use the Sepal and Petal measurements to predict the optimum number of clusters using the KMeans algorithm.

Regression, Classification and Clustering

Classifying chest X-ray images into two categories: Pneumonia or Normal using a Convolutional Neural Network (CNN).

Python Code for MKT - Consumer and Brand Research Course for Simon Business School

An overview of all clustering techniques available in sckit learn library with examples of data.

This project explores customer segmentation using various clustering techniques on a dataset of mall customers. The goal is to identify distinct customer groups based on demographic and behavioral attributes, enabling businesses to tailor their marketing strategies more effectively.

[Competition] 2022 FSI Data Challenge : 가계 기반 소비 활용 지표를 통한 지역별 Segmentation 및 ESG 경영서비스 제안

A Music Player with a Clustering based Recommendation Engine utilizing Spotify API

This repository focuses on building clustering algorithms from scratch using only Numpy for faster array processing.

UAV Power Consumtion for Survivability in WPT WSN application

K-means clustering algorithm implementation in Golang.

a kmeans algorithm proposed improvement