This repo contains the instructions for a machine learning project.
├── README.md <- The top-level README for describing highlights for using this ML project.
│
├── notebooks <- Jupyter notebooks. Naming convention should snake case.
│
├── reports
│ └── figures <- Generated graphics and figures to be used in reporting
│ └── README.md <- Youtube Video Link
│ └── final_project_report <- final report .pdf format and supporting files
│ └── presentation <- final power point presentation
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├── requirements.txt <- The requirements file for reproducing the analysis environment, e.g.
│ generated with `pip freeze > requirements.txt`
│
├── src <- Source code for use in this project.
├── __init__.py <- Makes src a Python module
├── data
│ ├── processed <- The final, canonical data sets for modeling.
│ └── raw <- The original, immutable data dump.
│
├── preprocessing_data <- Scripts to download or generate data and pre-process the data
│ └── pre-processing.py
│
├── feature_engineering <- Scripts to turn raw data into features for modeling
│ └── build_features.py
│
├── models <- Scripts to train models and then use trained models to make
│ │ predictions
│ ├── predict_model.py
│ └── train_model.py
│
└── visualization <- Scripts to create exploratory and results oriented visualizations
│ └── visualize.py
│
└── main.py <- main script to run all the models and call appropriate functions
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├── LICENSE <- LICENSE terms to be included for the use of the source code distribution