Hierarchical-Clustering

A tool to make dendograms from gene expressions.

Análise Kmeans e Dendograma de uma base de base de dados

This clustering analysis aims to provide valuable insights into the viability of introducing an original language cinema in Milan, Italy.

Mall Customer Segmentation Data

Clustering wedding guests.

Explore a comprehensive analysis of Netflix's extensive collection of movies and TV shows, clustering them into distinct categories. This GitHub repository contains all the details, code, and insights into how we've organized and grouped the vast content library into meaningful clusters.

This project is a step towards building an Artificial General Intelligence. The main goal is to discover an individual's biasses getting his/her field of interests from Instagram ad interests.

This is a R repository of studies that I made on some data sets. There are linear models, predicition models (boosting - bagging - RandomFlorest), clustering and dendograms.

This project aims to practice the steps of Crisp Data Mining ( CRISP-DM ). The repository includes 3 phases, data understanding, supervised learning, and unsupervised learning.

Superimpose a set of protein structures and report a RSMD matrix, in CSV and Mega-compatible formats, using Pymol as a module

Agglomerative Clustering from scratch without using built-in library with different hyper-parameters using Python and evaluated the cluster quality using intrinsic and extrinsic scores

Implemented K - means and Hierarchical clustering to cluster the retail customers into different segments, based on their spending habits. Employed RFM metrics and assigned labels to each customer based on RFM score.

Data prepration and preprocessing for predictive modeling with SAS and Python

The objective of this project is to categorise the countries using some socio-economic and health factors that determine the overall development of the country and then accordingly suggest the NGO the country which is in dire need of help.

Consensus Recommendation

Superimpose a set of protein structures and report a RSMD matrix, in CSV and Mega-compatible formats.

Used unsupervised machine learning, PCA algorithm, and K-Means clustering to analyze and classify a cryptocurrency database.