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 get the data, sign up for the competition and use the data download link!
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
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent