Capstone SwiftKey Project--Next Word Prediction

Coursera Data Science John Hopkins Capstone Project

• Natural language rocessing (NLP) and artificial intelligence (AI)
• You input the text, and we predict the next word.
• Shiny Web App
• Pitch Slides 5-pages

• Prediction algorithm: N-Grams
• Based on a subset of the given twitter, news and blog data
• N-Grams for 1 up tp 5 words were generated and saved as RData with the saveRDS function
• The app loads the saved models and uses them to make predictions

• The algorithm makes 5 suggestions for the next word
• It starts by using the most common 5 words from the training data as predictions/ recommendations
• Then it checks if there is one word typed inside the input field and whether there are predictions from the 2-Word-N-Gram for the given word
• And so on… Until 5-Word-N-Gram
• If the algorithm finds predictions from higher N-Grams it overwrites the old predictions
• If no prediction is found the most common words will be displayed as the suggestions

• The Shiny App has a Input-Text-Field for the input data and 5 buttons for the next word recommendations
• When the user types text into the input field the recommendations get automatically updated
• When the user clicks a button the recommendation is added to the input data (with a space if there isn't one)
• After clicking a button the input field is refocused so the user can continue to type without having to click on the input field again

• Shiny Web App: https://rjcc.shinyapps.io/Capstone_Swiftkey_RJCC/

• Pitch Slides: http://rpubs.com/rjcc/capstone_swiftkey_RJCC