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aledevans

Aled Evans

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R Presentation Pitch - Shiny App using NLP (Coursera Capstone)
A pitch presentation for a Shiny Application that uses natural language processing (NLP) for word prediction. This is the final part of the capstone project for the Data Science Specialization offered by Coursera & Johns Hopkins University (in association with Swiftkey). This R Presentation and capstone project - Aled Evans, March 2017.
Milestone Report - Capstone Project - Coursera Data Science
Milestone Report - Coursera - Capstone Project (Part of Coursera - Johns Hopkins University - Data Science Specialization) Author: Aled Evans The project is focused on developing a predictive text model using NLP (natural language processing) techniques. A large volume of text documents (referred to as the corpus) is analysed using NLP and to build the predictive text model. The text files used for the corpus are taken from US blogs, news and twitter – all of which are in the English language and supplied by SwiftKey. The milestone report briefly outlines the nature of the dataset / corpus and the results of exploratory data analysis. There is also a summary of the next steps for the development of the predictive model.
Developing Data Products - Shiny App - Final Project
Developing Data Products (Part of Coursera - Johns Hopkins University - Data Science Specialization) Author: Aled Evans
Scatterplot of US turnout data for 1992 Presidential election - Coursera
Plotly Interactive Scatterplot - Developing Data Products (Part of Coursera - Johns Hopkins University - Data Science Specialization) Author: Aled Evans Scatterplot (using Plotly ‘R’ package) of US turnout data for 1992 Presidential election. Age vs. Years of education. Color - Yellow for ‘Voted’; Purple for ‘Did not vote’
Leaflet Interactive Map - Coursera - Developing Data Products
Leaflet Interactive Map - Coursera - Developing Data Products (Part of Coursera - Johns Hopkins University - Data Science Specialization) Author: Aled Evans
Practical Machine Learning Project
Practical Machine Learning Project (Part of Coursera - Johns Hopkins University - Data Science Specialization) Author: Aled Evans This assignment focuses on fitness data gathered from accelerometers attached to different parts of the body. Using the data the assignment applies different machine learning models and identifies the best model for predicting the “classee” variable from a separate test dataset. The data was downloaded from: http://groupware.les.inf.puc-rio.br/har. (Human Activity recognition, Groupware @ LES - Weight Lifting Exercises Dataset). The Random Forest Model was selected (with the Generalized Boosted Model a very close second). The resulting predictions for “classe” in the test set scored 20 out of 20 - a 100% prediction succes
Regression Models Assignment - Coursera
Regression Models Assignment (Part of Coursera - Johns Hopkins University - Data Science Specialization) Author: Aled Evans Executive Summary The assignment examines a data set of a collection of cars and explores the relationship between a set of variables and miles per gallon (MPG).
Statistical Inference Course - Assignment 1
Statistical Inference Course - Assignment 1 Part of Coursera - Johns Hopkins University - Data Science Specialization “Aled Evans” Project Overview The project is an investigation of the exponential distribution in R and a comparison with the Central Limit Theorem.
Reproducible Research Course – Peer Assessment 2
Part of Coursera - Johns Hopkins University - Data Science Specialization. Reproducible Research Course – Peer Assessment 2. Author: Aled Evans