• Getting Started
• Running the App
• Tools Required
• Development
• Authors
  • Adam Broniewski
  • Chun Han (Spencer) Li
  • Himanshu Choudhary
  • Luiz Fonseca
  • Tejaswini Dhupad
  • Zyrako Musaj
• License
• Acknowledgments

This project has a stable branch called main. Different branches are created for during major changes to the model or for feature development.

The project follows the structure below:

	Child-Wasting-Prediction
	├── README.md
	├── LICENSE.md
	├── .gitignore
	└── notebooks
	└── src
		├── all executbale script files
	└── docs
		└── support documentation and project descriptions
	└── data
		├── raw
		└── processed

• Python
• Pip

1. Clone the project to a directory of your choice

   git clone https://github.com/abroniewski/Child-Wasting-Prediction.git

2. Pipenv is used to manage dependencies. If you do not have pipenv installed, run the following:

   pip install pipx
   pip install pipenv

3. Install dependencies using the included pipfile. Run the following from the parent directory.

   pipenv install
   pipenv run clean_notebook

4. Once all dependencies are installed, we can run the main file.

   python main.py

This will run the full data-preperation, model building and prediction generation using the data provided in /data.

No tools currently specified

The objective of this project is to work with various stakeholders to understand their needs and the impact modeling choices have on them. Additionally, the design choices are assessed through a lens of ethical impact.

The objective of the data analytics model to explore whether a better (more accurate or more generally applicable) forecasting model for predicting child watage can be developed, by researching one of the following two questions:

1. Is the quality of the additional data sources sufficient to improve or expand the existing GAM forecasting model? Are there additional, public data sources that allow you to improve or expand the existing GAM forecasting model?
2. Are there other techniques, different than additional data sources, that would lead to an improved GAM forecasting model on the data used in the development of the original GAM forecasting model?

Child-Wasting-Prediction is open source software licensed as MIT.

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