├── LICENSE
├── README.md          <- The top-level README for developers using this project.
├── data
│   ├── external       <- Other data, if needed
│   ├── processed      <- The final, canonical data sets for modeling.
│   └── raw            <- The original, immutable data dump from the numerai website
│
├── models             <- Trained and serialized models, dumped from TensorFlow, sklearn, etc.
│
├── notebooks          <- Jupyter notebooks for exploration
│
├── reports            <- Generated analysis as HTML, PDF, LaTeX, etc.
│   └── model_ouputs   <- Output of models, which include: ROC curve img, FPR, TPR, paraneters in JSON file,
│        │                submission file, validation predictions.
│        ├── MODEL_0
│        ├── MODEL_1
│         ...
│        └── MODEL_N
│
├── 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    
    │
    ├── data           <- Scripts to download or generate data
    │   └── make_dataset.py
    │
    ├── features       <- Scripts to turn raw data into features for modeling (empty)
    │   └── build_features.py
    │
    ├── models         <- Scripts to train models and then use trained models to make
    │   │                 predictions. Each model spcifies either a Neural Net architecture,
    │   │                 sklearn algorithm, etc.
    │   ├── base.py    <- A general purpose Base and Project class from which the MODEL_N inherits
    │   │                 from, where a variety of useful methods are implemented.
    │   ├── MODEL_1.py
    │   ├── MODEL_2.py
    │   ├── MODEL_3.py
    │   ├── MODEL_4.py
    │   └── __init__.py 
    │     
    └── utils
        ├── __init__.py 
        ├── definitions.py  <- File structure definitions
        └── utilities.py    <- General purpose scripts