Further student resources for DrivenData's 'Machine Learning with the Experts: School Budgets' DataCamp course.
To see the model, take a look at the notebook that builds the winning model.
To run the notebook, first install the dependencies with:
pip install -r requirements.txt
Then run:
jupyter notebook notebooks/1.0-full-model.ipynb
├── LICENSE
├── README.md
├── data
│ ├── TestSet.csv
│ └── TrainingSet.csv
├── notebooks
│ └── 1.0-full-model.ipynb
├── requirements.txt
└── src
├── __init__.py
├── data
│ └── multilabel.py
├── features
│ └── SparseInteractions.py
└── models
└── metrics.py
Project based on the cookiecutter data science project template. #cookiecutterdatascience