Boston Housing Price Prediction App

This project is a machine learning application built using Python, Tkinter for the GUI, and Scikit-learn for linear regression modeling. It predicts house prices based on three key features:

Number of rooms (RM)

Percentage of lower-class population (LSTAT)

Student-to-teacher ratio (PTRATIO)

The model is trained on the Boston Housing dataset, and users can input values through a user-friendly interface to get an estimated house price. The app is designed with a simple and intuitive layout for easy use.

Technologies Used:

Python

Pandas & NumPy (Data Processing)

Scikit-learn (Machine Learning)

Tkinter (GUI Development)

This project demonstrates skills in data preprocessing, model training, and interactive application development.