README.md 2.2 KB

canarie-energy-time-series-prediction

A deployable reference solution for DAIR participants to observe and study application of machine learning techniques in time-series predictions. This solution builds an energy load predictor.

Project Organization

├── LICENSE
├── Makefile           <- Makefile with commands like `make data` or `make model`
├── README.md          <- The top-level README for developers using this project.
│
├── data
│   ├── interim        <- Intermediate data that has been transformed.
│   ├── processed      <- The final, canonical data sets for modeling.
│   └── raw            <- The original, immutable data dump.
│
├── env.yaml           <- File to re-create development environment.
│
├── models             <- Trained models and model predictions
│
├── notebooks          <- Jupyter notebooks.
│
├── reports
│   └── figures        <- Generated graphics and figures to be used in reporting
│
└── src                <- Source code for use in this project.
    ├── __init__.py    <- Makes src a Python module
    │
    ├── data           <- Scripts to download or generate data
    │   └── make_dataset.py
    │
    ├── features       <- Scripts to turn raw data into features for modeling
    │   └── build_features.py
    │   └── select_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

Project based on the cookiecutter data science project template. #cookiecutterdatascience