House Price Prediction using Linear Regression

This repository contains my first and a simple machine learning model that predicts house prices based on the area of the house using a linear regression algorithm.

Project Overview

In this project, we train a linear regression model on a dataset of house prices. The model is then used to predict the prices of other houses based on their areas.

Dataset

• homePricesData.csv: Contains the area and corresponding prices of different houses, used for training the model.
• homePricePrediction.csv: Contains the areas of houses for which we want to predict the prices.

Libraries Used

• pandas for handling datasets
• numpy for numerical operations
• scikit-learn for machine learning algorithms (linear regression)
• matplotlib for data visualization

Code Explanation

1. Load and Visualize Data: We load the dataset and visualize it using a scatter plot to see the relationship between house area and price.
2. Train the Model: We train a linear regression model using the areas and prices.
3. Make Predictions: The model is then used to predict the prices of houses based on their areas from another dataset.
4. Save Predictions: The predicted prices are added as a new column in the dataset.

THANK YOU!