Data Science Capstone Final Assigment

Autor LinkedIn: https://www.linkedin.com/in/jose-javier-saravia-mata-01435a41/

• Take a sample less than 1% of all .txt (for avoid RAM problems)
• Transform to corpus and then remove punctuation and numbers
• Remove Profanity Words
• Create a tokenizer function
• Create 3:6 ngram token dataset
• Bind all ngram dataset and export to RDS
• Pre process data with personal script

readRDS("salida.rds")[1:3,]

            oracion          key2 freq2 pred2
1 happy mothers day happy mothers     6   day
2     new years eve     new years     5   eve
3   green cap kitty     green cap     4 kitty

• Clean Input
• Detect rows that contain the input
• Filter rows witg endsWith (input, row) == TRUE
• Aggregate sum of freq by keys of each row
• Calculate relative frequency for each result
• Show up to 5 rows (order by relative frequency desc)

• Put sentence to analice and then click on “Go”
• Remember that model is trained with 1% of .txt files (is possible that don't recognice some input sentences)
• App will show up to 5 answers order by relative frequency desc
• If you want to explore RDS model's dataset just use the slider which select some rows to print

App avaliable on: https://licjaviersaravia.shinyapps.io/CourseraCapstone/

Shiny APP: https://licjaviersaravia.shinyapps.io/CourseraCapstone/ Files: https://drive.google.com/drive/folders/1QxrrW6l-Ndwj2Ok-h6C_v7HoSGV9RjEG?usp=sharing