==============================
Text summarizing your project.
├── LICENSE
├── Makefile <- Makefile with commands like `make setup` or `make conda-create`
├── README.md <- The top-level README for developers using this project.
├── data
│ ├── external <- Data from third-party sources.
│ ├── interim <- Intermediate data that has been transformed.
│ ├── processed <- The final, canonical data sets for modeling.
│ └── raw <- The original, immutable data dump.
├── models <- Trained and serialized models, model predictions, or model summaries
│
├── notebooks <- Jupyter notebooks. The naming convention is a date (for ordering),
│ the creator's initials, and a short `-` delimited description, e.g.
│ `03132024-pranav-data-exploration`.
│
├── references <- Data dictionaries, manuals, and all other explanatory materials.
│
├── reports <- Generated analysis as HTML, PDF, LaTeX, etc.
│ └── figures <- Generated graphics and figures to be used in reporting
│
├── environment.yml <- The environment file for reproducing the analysis environment, e.g.
│ generated with `conda create -f environment.yml`
│
├── src <- Source code for use in this project.
│ ├── __init__.py <- Makes src a Python module
│ │
│ ├── data <- Scripts to process data
│ │
│ ├── models <- Scripts to train models and then use trained models to make
│ │ │ predictions
│ │
│ └── visualization <- Scripts to create exploratory and results-oriented visualizations
- Clone the repo
- Create a virtual environment
- Install the requirements
- Run the notebooks
git clone
cd EpiPandit_Template
make conda-create
conda activate EpiPandit_Template
make setup
jupyter notebookProject based on the cookiecutter data science project template.