Publications by Mark Edney
NOAA Storm Data Analysis
Synopsis Data on different storm events have been collected by the National Oceanic and Atmospheric Administration (NOAA)1 starting in the 1950s. Through the careful cleaning and analysis of the collected storm data, one event takes precedence over all others. Tornadoes have the highest effect of human health with high levels of fatalities and in...
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Data products assignment 3
07/01/2021 Objective The objective of this presentation is to present the Covid cases data from Open Toronto using the Plotly package. Installing Packages The following code is used to install the necessary packages install.packages("opendatatoronto", repos = "http://cran.us.r-project.org", dependencies = TRUE) library(opendat...
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Speed camera ins Toronto
Objective This report plots the speed cameras in the Greater Toronto Area from the data provided by Open Toronto which can be found here. Inialization The following code is used to inialize the required libraries. install.packages("opendatatoronto", repos = "http://cran.us.r-project.org", dependencies = TRUE) package 'opendatatoronto' successful...
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Toronto Bike
14/01/2021 Bike Rental Shiny App This application use the data collected from the Toronto Open Data to generate a histogram of the usage of rental bikes in Toronto during the month of June in 2020. install.packages("opendatatoronto", repos = "http://cran.us.r-project.org", dependencies = TRUE) library(openda...
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Milestone Report
Obejective The objective of this milestone report is to outline the steps for data analysis for the Capstone project for the data science course on Coursera by John Hopkins University. The Project is to create a text predicting algorithm based on a Corpus created from three different data sets. Initialization The following code load the required...
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Predictive Text Slide Deck
Predictive Text Slide Deck Mark Edney 22/05/2021 Predictive Text Application The Predictive Text Application accepts text from the user and predicts the next word from five different models: the Maximum Likeliness Estimate, Add One, Good Turing estimate, Absolute Discounting Interpolation and Kneser Ney Smoothing. These models perform automat...
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Machine Learning Final Project
Executive Summary This report analyzes collected data on different users preforming barbell lifts preformed at different levels of quality. A machine learning algorithm was used to create a model to determine the users rating based on data collected from multiple accelerometers. More information on the project can be found here. Analysis Initia...
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