Slide 1: Project Overview

• Goal: Create a product that demonstrates a predictive text algorithm.
• Deliverables:
  • A Shiny app for next-word prediction.
  • A slide deck to present the algorithm and app.

Slide 2: Algorithm Details

• N-gram Model:
  • Based on trigrams (sequences of three words).
  • Predicts the next word using the last two words of a given phrase.
• Data Sources:
  • Blogs, news articles, and tweets.
• Preprocessing:
  • Tokenization, cleaning, and frequency analysis.

Slide 3: Shiny App Features

• Functionality:
  • Input: Enter a phrase in the text box.
  • Output: Predict the next word.
• User Experience:
  • Simple and intuitive interface.
  • Fast and responsive predictions.

Slide 4: How to Use

1. Open the app in your browser.
2. Enter a phrase in the text box.
3. Click “Predict” to view the next word.

Slide 5: Conclusion

• Impact: Enhances user productivity by predicting text efficiently.
• Applications:
  • Chatbots, typing assistants, and autocomplete features.
• Future Work:
  • Expand to multilingual support.
  • Improve accuracy with deep learning models.