2023-TAMIDS-Competition-Data

Datasets and Executable codes for 2023 TAMIDS Data Science Competition (Team - Sam's Strikers)

Awarded 3rd place in the graduate competition.

Best supplementary materials award.

Best mid-point visualization award.

Folder Structure -

1. R - Codes for initial data analysis and preparation. Downloading and cleaning remote sensing datasets, and plotting figures.
2. shiny-app - R code for shiny web application https://shubhamjain.shinyapps.io/Wildfires/
3. Plots - saves png files for plots in report
4. GIS_data - geodatabase for GIS data used in analysis and arcpro map project files for map preparation
5. DNN_model - Executable Python notebook to run Deep Neural Network (DNN) model
6. wildfires_data.csv - Dataset prepared for DNN model
7. TAMIDS_2023_SAMS_STRIKERS.pdf - Final Report