Data analysis to predict human activity recognition

Slidy User Guide that explains how to use the Random Forest Grid Search Simulator Shiny App.

This presentation contains a Plotly scatter plot from a residual analysis for house price predictions in Buenos Aires, Argentina. Data can be downloaded from Properati web page (https://www.properati.com.ar/data/). R Markdown and other files required to generate this presentation are provided in the following Github repo: https://github.com/ricardoleoncorreia/data-science-portfolio/tree/master/plotly-ba-houses-prediction-residual-analysis.

Acamica Data Science Career Project 2 presentation. This is the second part of a project to build a house price predictor. The goal is to present a demo (SCRUM) a 10 min analysis of the problem (current results and todos).

Interactive Leaflet-based map showing house details in Buenos Aires, Argentina.

Every year natural disasters produce a wide variaty of loses. Two of them are the subject to study in this report, injuries and fatalities and properties and crops damages. Using R libraries to process data (dplyr) and plot results (ggplot2) will help us to find out the most harmful event and the one with the greatest economics consequences. At the end, we get that tornados causes the most injuries and fatalities of all events and floods causes the greatest economics consequences.