https://github.com/datacamp/course-resources-ml-with-experts-budgets
Further student resources for DrivenData's 'Machine Learning with the Experts: School Budgets' DataCamp course.
https://github.com/datacamp/course-resources-ml-with-experts-budgets
Last synced: about 1 year ago
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Further student resources for DrivenData's 'Machine Learning with the Experts: School Budgets' DataCamp course.
- Host: GitHub
- URL: https://github.com/datacamp/course-resources-ml-with-experts-budgets
- Owner: datacamp
- License: mit
- Created: 2017-03-02T13:10:27.000Z (over 9 years ago)
- Default Branch: master
- Last Pushed: 2017-12-14T20:46:55.000Z (over 8 years ago)
- Last Synced: 2025-04-04T05:45:56.867Z (about 1 year ago)
- Language: Jupyter Notebook
- Size: 11.7 KB
- Stars: 557
- Watchers: 37
- Forks: 631
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# course-resources-ml-with-experts-budgets
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](notebooks/1.0-full-model.ipynb).
To get the data, sign up for [the competition](https://www.drivendata.org/competitions/46/box-plots-for-education-reboot/) 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
Project Organization
------------
├── 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
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Project based on the cookiecutter data science project template. #cookiecutterdatascience