House Price Prediction Project

This Python project aims to predict the prices of houses based on various features using machine learning techniques. The dataset used for this project contains information about different houses including their size, location, number of bedrooms, number of bathrooms, etc. The goal is to build a model that can accurately predict the price of a house given its features.

Dataset

The dataset used for this project is named house_prices.csv. It contains the following columns:

id: Unique identifier for each house lot_size: Size of the lot in square feet neighborhood: The neighborhood where the house is located num_bedrooms: Number of bedrooms in the house num_bathrooms: Number of bathrooms in the house year_built: Year the house was built sale_price: Sale price of the house (target variable)