box-plots-sklearn
A scikit learn implementation of the winning algorithms for the Box Plots for Education competition.
Project Organization
βββ LICENSE
βββ Makefile <- Makefile with commands like `make data` or `make train`
βββ README.md <- The top-level README for developers using this project.
βββ data
βΒ Β βββ external <- Data from third party sources.
βΒ Β βββ interim <- Intermediate data that has been transformed.
βΒ Β βββ processed <- The final, canonical data sets for modeling.
βΒ Β βββ raw <- The original, immutable data dump.
β
βββ requirements.txt <- The requirements file for reproducing the analysis environment, e.g.
β generated with `pip freeze > requirements.txt`
β
βββ src <- Source code for use in this project.
βΒ Β βββ __init__.py <- Makes src a Python module
β β
βΒ Β βββ data <- Scripts to download or generate data
βΒ Β βΒ Β βββ make_dataset.py
β β
βΒ Β βββ features <- Scripts to turn raw data into features for modeling
βΒ Β βΒ Β βββ build_features.py
β β
βΒ Β βββ models <- Scripts to train models and then use trained models to make
β β β predictions
βΒ Β βΒ Β βββ predict_model.py
βΒ Β βΒ Β βββ train_model.py
β
Project based on the cookiecutter data science project template. #cookiecutterdatascience