Utilizing Polynomial Regression and XGBoost for Optimized Lignocellulosic Derivative Adsorption in Water Treatment with Ficus Nitida Activated Charcoal

This project was done to powerfully participate in the TeqFest AI and Sustainable Development Goals Hackathon at the American University in Cairo (AUC)-winning 1st place. In these intensive five days (13 -->> 18 April) hackathon we are working on data collection, preprocessing the data, testing, and developing the model (mathematically and at the implementation level using Python). Finally, We came up with this humble project!

A comprehensive overview of the proposed pipeline, explaining the different stages of analyzing the inputs, classifying, finding the relation and predicting the adsorption capacity of Ficus Nitida.