Instructions

The goal of this exercise is to create a product to highlight the prediction algorithm that you have built and to provide an interface that can be accessed by others. For this project you must submit:

• A Shiny app that takes as input a phrase (multiple words) in a text box input and outputs a prediction of the next word.
• A slide deck consisting of no more than 5 slides created with R Studio Presenter pitching your algorithm and app as if you were presenting to your boss or an investor.

Data Product

• Does the link lead to a Shiny app with a text input box that is running on shinyapps.io?
• Does the app load to the point where it can accept input?
• When you type a phrase in the input box do you get a prediction of a single word after pressing submit and/or a suitable delay for the model to compute the answer?
• Put five phrases drawn from Twitter or news articles in English leaving out the last word. Did it give a prediction for every one?

• Does the link lead to a 5 slide deck on R Pubs?
• Does the slide deck contain a description of the algorithm used to make the prediction?
• Does the slide deck describe the app, give instructions, and describe how it functions?
• How would you describe the experience of using this app?
• Does the app present a novel approach and/or is particularly well done?
• Would you hire this person for your own data science startup company?

In the shiny app, users can casually key in any character inside text box. The the system will auto appear the suggested next predictive words in table format by follow the most accurate in sequence. You can show/hide the author and source code link if you like.

I am using tm and RWeka packages for previous assignments, but occassionaly noticed a new package quanteda which is more efficient and clean, clear and concise and text mining and n-grams words prediction. At the same time I am using shinyjs package to come out with better output and interactive. I’ve removed the graphs while you can refer to Natural Language Analysis if you’ld like to.

You are feel free to browse over the shiny app at Final Project-Submission (Shiny App).

It’s useful to record some information about how your file was created.

• File creation date: 2015-07-22
• File latest updated date: 2020-11-18
• R version 3.6.3 (2020-02-29)
• R version (short form): 3.6.3
• revealjs package version: 0.9
• File version: 1.0.0
• Author Profile: [Harry Maan]
• GitHub: Source Code
• Additional session information:

[1] “2020-11-18 11:20:43 IST” setting value
version R version 3.6.3 (2020-02-29) os macOS Catalina 10.15.7
system x86_64, darwin15.6.0
ui X11
language (EN)
collate en_US.UTF-8
ctype en_US.UTF-8
tz Asia/Kolkata
date 2020-11-18
sysname “Darwin” release “19.6.0” version “Darwin Kernel Version 19.6.0: Thu Oct 29 22:56:45 PDT 2020; root:xnu-6153.141.2.2~1/RELEASE_X86_64” nodename “Harry-Maans-MacBook-Air.local” machine “x86_64” login “root” user “harrymaan” effective_user “harrymaan”