Claudio Sebastián Castillo, 2019
The Data Science Specialization Capstone Project from Johns Hopkins University and Coursera is focus in the Natural Language Processing domain. The goal of this project is to create an application that predict the next word from a corpus called. For make that prediction Natural Language Processing techniques were used.
The aplication is based on sampled data from diferent source (News, Twitter and Blog), processed appropriately for analysis, and tokenized into n-grams. Using that subset of cleaned data we computed Maximum Likelihood Estimation (MLE) of unigrams, bigrams, and trigrams. We improve accuracy with Jelinek-Mercer smoothing algorithm.
The aplication is a simple user interface that take an text imput and generate a predicted word as output.
Application is running at: https://castillocs.shinyapps.io/shiny_app/
Github link for various code files is here: https://github.com/castillosebastian/NLP_Project