DSFSI Project Starter

This documentation is aimed to help provide information that explains what a project is about.

Last updated: August 2023

Table of contents

1. Project Description
2. Project Organization
3. Getting Started
4. Authors
5. More Information

Project Description

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A short description of the project.

Project Organization

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├── LICENSE
├── Makefile           <- Makefile with commands like `make data` or `make train`
├── 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.
│
├── docs               <- A default Sphinx project; see sphinx-doc.org for details
│
├── models             <- Trained and serialized models, model predictions, or model summaries
│
├── notebooks          <- Jupyter notebooks. Naming convention is a number (for ordering),
│                         the creator's initials, and a short `-` delimited description, e.g.
│                         `1.0-jqp-initial-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
│
├── requirements.txt   <- The requirements file for reproducing the analysis environment, e.g.
│                         generated with `pip freeze > requirements.txt`
│
├── setup.py           <- makes project pip installable (pip install -e .) so src can be imported
├── 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
│   │
│   ├── 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
│
└── tox.ini            <- tox file with settings for running tox; see tox.testrun.org

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

Getting Started

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This section provides the necessary information for a user to be able to run the code locally.

Prerequisites

Provide a summary of the list software and the version required to run the code. An example of this is :

• Python 3.11.3

Installation

Provide the instructions and code necessary to setup the required software environment for the code. An example of this is :

1. Run the setup.py to build the src python package
2. Run the requirements.txt to install all the required libraries, modules, and packages.

python setup.py install
pip install -r requirements.txt 

Usage

Provide information and code on how to run the code and use the code. This includes instructions and examples of inputs and outputs. An example of this is :

1. To use the code , run the following line:

python src/main.py

Authors

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• Written by :
• Contact details :

Contributions

This is optional and provides information about which and how each of the developers contributed.

More Information

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Provide any relevant informations about the project.