Spiro Kolokithas

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Developing Data Products Week 4 Assignment
A Shinny App modelling electricity usage of house based on forecast weather.
Practical Machine Learning Assignment
sing 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, the goal will be to use data from accelerometers on the belt, forearm, arm, and dumbell of 6 participants. The goal of the assignment is to predict the manner in which they did the exercise. This is the “classe” variable in the training set. The prediction model will be used to predict the method of exercise. This assignment will use a number of models and perform final predictions with the model deemed to have the best accuracy.
Assignment: Regression Models Course Project
Analysis of MT Cars
Reproducible Research Peer Assessment 2
Storms and other severe weather events can cause both public health and economic problems for communities and municipalities. Many severe events can result in fatalities, injuries, and property damage, and preventing such outcomes to the extent possible is a key concern. This project involves exploring the U.S. National Oceanic and Atmospheric Administration's (NOAA) storm database. This database tracks characteristics of major storms and weather events in the United States, including when and where they occur, as well as estimates of any fatalities, injuries, and property damage.