(https://github.com/akselix/capstone_swiftkey)
This project was the final part of a 10 course Data Science track by Johns Hopkins University on Coursera. It was done as an industry partnership with SwiftKey. The job was to clean and analyze a large corpus of unstructured text and build a word prediction model and use it in a web application.
More info here: (http://rpubs.com/akselix/word_prediction)
Shiny app
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Data is preloaded into (./shiny/data/)
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./shiny/prediction.R
- Contains most of the functions used by the other scripts
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./shiny/server.R
- Contains the server side functions
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./shiny/ui.R
- Handles the input/output
Preparing the data and validation
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./shiny/prediction.R
- Contains most of the functions used by the other scripts
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./prepare_data.R
- Data is cleaned and tokenized with this
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./test_prediction.R
- Run manual tests
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./validation.R
- Run an automated accuracy calculation on validation data