The goal of the job is to create models to predict prices of houses and apartments located in Capital Federal, Argentina. Different models will be performed and then the best one will be selected. The models proposed are: Linear Regression, KNN and Decision Trees (using Random Forest and boosting methods). The best model is select by RMSE criteria

The goal of the job is to get the probability of being a victim of a crime on each suburb of Buenos Aires city for a specific time zone. The probabilities are calculated by Bayes Theorem. Clustering methods are also applied to cluster zones with high, medium and low rate of crime. Graphics are made by using of plotly library

The goal of the job is to render a map of Buenos Aires city showing where is permitted to park on public areas The data is available from the Buenos Aires government web