EDA, data processing, cleaning and extensive geospatial analysis on a selenium based web scraped dataset

Bayesian Hierarchical Clustering

GUI version of https://github.com/guglielmosanchini/ClustViz

Hierarchical and K-Means Clustering in R and application to California housing data

Customers RFM Clustering (Market Segmentation based on Behavioral Approach)

Time Series Clustering using Hierarchical Clustering (Agglomerative and Divisive)

Clustering analysis on the data from the World Happiness Report 2021.

Apresentação: Cluster e segmentação de clientes

A library of implementations in the 'iads' directory, plus Jupyter notebooks for testing

This repository gives you access to the CLIMATEREADY survey dataset containing thermal comfort votes during the 2021 and 2022 heatwave periods in Pamplona, Spain, as well as other relevant parameters self-reported by surveyees (e.g. occupant characteristics and behaviour, key building/dwelling characteristics, sleep problems, heat-related symptoms)

Data Visualizations from my Master's thesis.

To use dataset provided in https://worldhappiness.report for years 2008-2020 to create a machine learning algorithm that can predict one's happiness score based on the criterias given in the report. Furthermore, a website is created to showcase the machine learning algorithm and various plots.

Contains code to run and visualize techniques like Clustering, PCA, Generative Modeling on publicly available data.

Clustering

Classification Model of Potential Credit Card Customers

School Safety Study of 2014 in the New York City

Exploratory data analysis with hierarchical clustering on data from Rotten Tomatoes about Jake Gyllenhaal’s movies

Using linear ordering to prepare the ranking of cyclist-friendly places in Poland and grouping them with (hierarchical) cluster analysis

Applying data mining techniques to a set of documents to determine meaningful relationships between them.

Illustrative analysis showing how population genetic structure discovery in Plasmodium genetic data using principal coordinates analysis and hierarchical clustering is sensitive to the pairwise genetic distance and the clustering linkage function