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Water Quality Prediction

This project combines machine learning and a Java GUI to create an application that predicts water potability based on various water quality parameters.

Project Structure

1. water_quality_model.pkl: Pre-trained machine learning model for water quality prediction.
2. scaler.pkl: Scaling logic for normalizing input data.
3. water_potability.csv: Dataset containing water quality parameters like pH, Hardness, etc.
4. train_model.py: Python script to train the machine learning model.
5. predict.py: Python script for making batch predictions using the trained model.
6. predict_water_quality.py: Python script to streamline the prediction process, possibly used for CLI.
7. background.jpg: Background image used for the GUI.
8. WaterQualityGUI.java: Java Swing-based GUI for inputting water parameters and receiving predictions.
9. Compiled Classes:
   • WaterQualityGUI.class: Compiled Java GUI classes.

Features

• Machine Learning: Predicts water potability based on key parameters.
• Interactive GUI: User-friendly Java-based interface for input and output.
• Python Integration: Model training and predictions handled in Python, integrated with Java.

How to Run

1. Python Setup:

   • Install dependencies:

     pip install pandas scikit-learn

   • Train the model:

     python train_model.py

   • Test predictions:

     python predict.py

2. Java Setup:

   • Compile the GUI:

     javac WaterQualityGUI.java

   • Run the GUI:

     java WaterQualityGUI

3. Ensure Integration:

   • Verify Python and Java paths for seamless interaction.

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