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Tarea 1 Modulo 1 PEEA 2022
PEEA de la UNI
Machine learning Modulo2
Final report
Innovacion Empresarial 2018
Universidad Nacional de San Agustin de Arequipa
Facultad de Economia
MOOC Econometrics Exam 1
Test Exercise 1
Final Project Development Product
Final Presentacion about my Shiny App
Final project on Machine Learning
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, your goal will be to use data from accelerometers on the belt, forearm, arm, and dumbell of 6 participants. They were asked to perform barbell lifts correctly and incorrectly in 5 different ways. More information is available from the website here: http://groupware.les.inf.puc-rio.br/har (see the section on the Weight Lifting Exercise Dataset).
Project1: Simulation and Basic Statistic Inference
Project Part1
NOAA Storm Analysis
The basic goal of this assignment is to explore the NOAA Storm Database and answer some basic questions about severe weather events. You must use the database to answer the questions below and show the code for your entire analysis. Your analysis can consist of tables, figures, or other summaries. You may use any R package you want to support your analysis.