mohamed-em2m / water-quality-and-potability

Water Quality Classification Project

This repository contains a machine learning project that focuses on classifying water quality as potable or non-potable based on a given dataset. It includes data preprocessing, model selection, training, evaluation, and visualization.

Table of Contents

• Introduction
• Dataset
• Usage
• Project Structure
• Dependencies
• Installation
• Getting Started
• Results
• Contributing
• License

Introduction

Water quality is an essential aspect of public health. This machine learning project aims to classify water samples as potable or non-potable based on various features, such as pH, solids, and more. It explores different machine learning algorithms, performs data analysis, and evaluates model performance.

Dataset

The dataset used for this project is available here. It contains information about water quality attributes and whether the water is potable or not.

Usage

This project can serve as a starting point for anyone interested in water quality classification tasks. You can use the provided code to:

• Explore and preprocess the dataset.
• Train and evaluate various machine learning models.
• Visualize the results using ROC curves, Precision-Recall curves, and other plots.

Project Structure

• data/: Contains the dataset used in the project.
• notebooks/: Jupyter notebooks for data exploration, model training, and evaluation.
• scripts/: Python scripts for data preprocessing, visualization, and model training.
• README.md: The main documentation file you're currently reading.

Dependencies

This project relies on the following Python libraries:

• NumPy
• pandas
• Matplotlib
• Seaborn
• Plotly
• scikit-learn
• XGBoost

You can install these dependencies using the instructions in the next section.

Installation

To set up this project locally, follow these steps:

1. Clone this repository to your local machine:

   git clone https://github.com/your-username/water-quality-classification.git