Coursera Data Science Capstone Project - Part-II

If you wish t o try out the app, clic k on the link https://joejokelly.shinyapps.io/Capstone-Project-work/

• The app predicts the next word as the user type a word or a group of words.
• The app used the Swiftkey technology

Instructions

The original data was sampled from three sources, (blogs, twitter and new) which is later merged into one

• Next, data cleaning is done, stipping white space, conversion to lowercase, removing punctuation and numbers. Later after the process is completed, n-grams are created (Quadgram, Trigram and Bigram).
• Next, the count tables are extracted from N-Grams, and sorted with frequency in descending order.
• The final process is the n-grams are saved into R-compressed files, (.RData files).

• Checks if highest-order (in this case, n=4) n-gram has been seen. If not “degrades” to a lower-order model (n=3, 2); we would use even higher orders, the maximum ShinyApp size is 100mb.