The Systematic Heat Analysis and Data Evaluation Project @ Texas A&M University.
Predictive modeling for heat waves, analyzing time-series temperature data from Austin, TX (1999-2023).
Naming convention for all files is team name, a number (for ordering), and a short - delimited description, e.g. ml-1.0-initial-data-exploration.ipynb or hybrid-1.0-heatmap-calendar.png.
├── Makefile
├── README.md <- The top-level README for developers using this project.
│
├── models <- Trained and serialized models, model predictions, or model summaries
│
├── notebooks <- Jupyter notebooks. Naming convention is team name, a number (for ordering),
│ and a short `-` delimited description, e.g.
│ `ml-1.0-initial-data-exploration`.
│
├── pyproject.toml <- Project configuration file with package metadata
│
├── references <- Data dictionaries, manuals, and all other explanatory materials.
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├── reports <- Generated analysis as HTML, PDF, LaTeX, etc.
│ └── figures <- Generated graphics and figures to be used in reporting
│
├── requirements.txt <- The requirements file for reproducing the analysis environment, e.g.
│ generated with `pip freeze > requirements.txt`
│
├── setup.cfg <- Configuration file for flake8
│
└── the_s.h.a.d.e._project___adsc_f25 <- Source code for use in this project.
│
├── __init__.py <- Makes the_s.h.a.d.e._project___adsc_f25 a Python module
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├── config.py <- Store useful variables and configuration
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├── dataset.py <- Scripts to download or generate data
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├── features.py <- Code to create features for modeling
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├── modeling
│ ├── __init__.py
│ ├── predict.py <- Code to run model inference with trained models
│ └── train.py <- Code to train models
│
└── plots.py <- Code to create visualizations