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Capstone- presentation- text predictors
This presentation introduces a Predictive Text Model designed to predict the next word in a user-provided phrase. Built using N-gram Language Modeling (unigrams, bigrams, and trigrams), the model leverages real-world text data sourced from blogs, news articles, and Twitter. The model is deployed as an interactive Shiny App that provides real-time word predictions, enhancing typing efficiency and user experience.
Online Text Exploration
This is an analysis of three corpora of US English text found online. The blogs and news corpora are similar, but the Twitter corpus differs. We propose that this results from the character limit of Twitter messages.
presentation
presentation
R Markdown Presentation & Plotly
using R Markdown that features a plot created with Plotly. Host your webpage on either GitHub Pages, RPubs, or NeoCities. Your webpage must contain the date that you created the document, and it must contain a plot created with Plotly.
Document
Developing Data Products
Module 3
R Markdown and Leaflet
Fit_Project_MachineLearning
With the birth of wearable devices such as Jawbone Up, Nike FuelBand, and Fitbit, collecting extensive data on personal activity has become increasingly popular. These devices are central to quantified self-movement, where individuals routinely track their data to enhance their health, identify behavioral patterns, or simply out of interest in technology. While many users focus on quantifying the frequency of their activities, they often need to pay more attention to the quality of their performance.
This project aims to bridge that gap by analyzing data collected from six participants’ accelerometers placed in their belts, forearms, arms, and dumbbells. These participants performed instructed barbell lifts correctly and incorrectly in five distinct ways.
Final Report: Impact of Severe Weather Events on Public Health and Economic Consequences
Introduction
Severe weather events such as storms can result in significant public health and economic challenges for communities. Fatalities, injuries, and property damage are common outcomes of such events, and minimizing their impact is a priority for disaster preparedness and response. This report analyzes data from the U.S. National Oceanic and Atmospheric Administration's (NOAA) storm database to understand the types of weather events that most affect population health and have the greatest economic consequences.