• Built as part of Coursera Data Science Capstone
• Predicts the next word in a user-entered phrase
• Uses blogs text dataset is used.

• Text cleaned and tokenized using tidytext
• Created unigram, bigram, and trigram frequency tables
• Uses n-gram model with backoff:
  • If trigram not found → backoff to bigram → backoff to unigram

Prediction Model

• Efficient and memory-optimized using RDS storage
• Fast lookup using dplyr filtering and slice_max
• Handles unknown inputs with fallback strategy

• Built using Shiny and hosted on shinyapps.io
• User enters a phrase → App predicts the next word
• Try it live here:
  https://x1tkzd-anila-mohanan.shinyapps.io/NextWordPredictor/

• Accurate, fast predictions with minimal resources
• Real-time prediction from cleaned social and web text
• Could be extended into mobile keyboards or chat assistants