Code and data for evaluating predictive models of the rent data set

1. This html file contains most of the results in static html.
2. The source code in Quarto. Most of the code was written by ChatGPT.
3. To further visializing the predictions and biases, a Shiny app is deployed at https://bioge.shinyapps.io/rent23/. The app.R file is the source code.

Congratulation to Daniel Burkhalter and Noah Stewart for winning the 2023 competition! Akin & Mitu is at second place. Addy's model is at 3rd place. The top 8 models are actually very successful in predicting rent with about 30-33% error. Congratulations to all for successfully completing this project.