HOUSE PRICE PREDICTION MODEL BY PROTYUSH MITRA

A simple and clean Python project that predicts house prices based on features like area, number of bedrooms, bathrooms, stories, and parking. It is a real world problem that requires various concepts from the course Fundamentals of AI/ML such as Linear Regression.

PROJECT OVERVIEW

This project uses Linear Regression to predict house prices in India (in Rs).

• It trains on real house data from data.csv
• Shows actual vs predicted prices in a clean table
• Displays a visual comparison graph

FEATURES

• Loads and cleans the dataset automatically
• Trains a Linear Regression model
• Predicts house prices
• Shows first 100 predictions with original full prices
• Displays a scatter plot comparing actual vs predicted prices (in Lakhs)

REQUIREMENTS

You need to have these installed:

• Python 3.8 or higher
• The following libraries:

  pandas
  scikit-learn
  matplotlib
  

HOW TO RUN THIS

• Clone or download this repository.

• Open the folder in Visual Studio Code.

• Make sure both files are in the same folder: Main.py data.csv

• Open the Python file and run it

You will see:

• A message saying how many rows were loaded
• A table with Actual Price vs Predicted Price (first 100 rows)
• A scatter plot comparing actual vs predicted prices (in lakhs)

FILES IN THIS REPOSITORY

• data.csv → House price dataset
• Main.py → Main Python script with full comments to increase the readability of the code for a even a beginner
• README.md → File that gives the whole description about this project (This file)

SCATTER PLOT GRAPH

• Black dots = Actual house prices
• Orange stars = Predicted prices

TECHNOLOGIES USED

• Python
• Pandas (data handling)
• Scikit-learn (Linear Regression)
• Matplotlib (visualization)

THANK YOU

Feel free to explore, run it yourself and suggest improvements.

MADE BY PROTYUSH MITRA 25BAI10024