• Brief description of the problem and presentation of the application.
• Mention of using language models and N-grams for predicting the next word.
• Mention of using the shiny, tm, and quanteda packages in developing the application.

• Overview of the raw data (in this case, a small corpus of texts in English).
• Text preprocessing: converting to lowercase, removing punctuation and numbers, removing stopwords, stemming.
• Creating an N-gram model based on the data.

• Show a screenshot of the user interface with a text input field and a button for processing.
• Explain how the user can use the application to predict the next word in the text.

• Overview of the main steps in the application code.
• Explanation of how the prediction function works and how the model is called.
• Mention of using the tm and quanteda libraries for text preprocessing and N-gram model creation.

here is my app: https://dgasoskov.shinyapps.io/title/

• Summary of using the Shiny application for word prediction.
• Discussion of possible improvements and future directions for the application (e.g., adding more data, improving language modeling, etc.).
• Invitation to questions and discussion.