DynamicRythms is a data-centric research project that investigates the predictive relationship between rare weather events and power outages. This repository contains all the essential code and resources for training and evaluating deep learning and gradient boosting models to empirically validate this correlation.
The repository is organized into the following directories:
- Documents/: Contains documents and figures related to the project.
- EDA/: Notebooks and scripts for exploratory data analysis.
- Modeling/: Includes modeling scripts, data merging, and feature generation.
- OldCode/: Archive of legacy code from earlier project iterations.
Additional files in the root directory:
- README: Project overview and instructions.
- requirements.txt: List of Python dependencies required to run the project.
- .gitignore: Specifies files and directories to be ignored by Git.
- Python 3.7 or higher
- Recommended: Create a virtual environment to manage dependencies
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Clone the repository:
git clone https://github.com/obelisk2u/DynamicRythms.git cd DynamicRythms -
Install dependencies
pip install -r requirements.txt
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Drop data Drop the data/ folder from the challenge website into /DynamicRythms. It's not included in the repo due to size restrictions.