This project heavily focuses on the construction of different classification models in order to accurately predict the satisfaction level of a client for a specific airline.

This project focuses on the implementation of different linear regression models that attempt to provide an accurate prediction and description of a newborn's weight in the city of Medellin, Colombia.

This project showcases the utilization of k-means, an unsupervised learning algorithm used to classify data into clusters, on SQL-extracted data from a database connection. In order to better understand the behavior of the differnet types of clients that buy products in a certain business.

The project briefly shows NLP techniques and its procedures (including bag of words and tf-idf) in order to create a predicting model to classify covid-related tweets as positive, negative or neutral.

This project tries to find and explain the possible relation between the proportion of female participation in politics and the implementation of term limits by using linear models; including a variety of different linear models to choose from (OLS and GAMLSS).

Project regarding sampling for unspecified distributions, using the inverse transform method and the rejection method. This was developed as a freelance project for a client.

En este proyecto se busca entender más acerca de la distribución de los árboles de la especie Abarco en la ciudad de Medellín, con la idea de buscar formas de cuidarlos de la extinción.

En este trabajo se presenta un análisis espacial sobre la precipitación en el país africano de Ethiopia. Para llegar finalmente a predecir el valor de esta en cada punto del país.

En este proyecto se busca dar una amplio contexto histórico acerca de los automóviles y su importancia global, para posteriormente utilizar técnicas bayesianas, e incluyendo información a priori, con el fin de construir un modelo lineal que prediga el precio de un Renault Logan según su año de salida.