The goal of the capstone project is to create a predictive text model using a large text corpus of documents as training data.

In this document some word analysis is made with unigrams, bigrams and trigrams plots. Moving forward, the project goal is to develop a natural language prediction algorithm and shiny app.

In this application, you can obtain an scatterplot with the two variables you want of the "concreteAll" dataset from "fastR" package.

In this interactive map we can see the horsepower and miles per gallon by number of cylinders from mtcars dataset.

In this project, we are going to create an interactive map of Real Madrid's Stadium location.

Using devices such as Jawbone Up, Nike FuelBand, and Fitbit it is now possible to collect a large amount of data about personal activity relatively inexpensively. These type of devices are part of the quantified self movement - a group of enthusiasts who take measurements about themselves regularly to improve their health, to find patterns in their behavior, or because they are tech geeks. One thing that people regularly do is quantify how much of a particular activity they do, but they rarely quantify how well they do it.

In this project we are going to work for Motor Trend, a magazine about the automobile industry. They are interested in knowing if an automatic transmission is better than manual transmission better for MPG?

In this project we are going to investigate the exponential distribution in R and compare it with the Central Limit Theorem

ToothGrowth Data Analysis in the R datasets package

Reproducible Research_Course Project 2