House Price Prediction

This project aims to predict house prices using various machine learning models. The project includes exploratory data analysis (EDA) and model training.

Requirements

To install the required packages, run:

pip install -r requirements.txt 

or use

pip freeze > requirements.txt

Exploratory Data Analysis (EDA)

The EDA section includes various analyses and visualizations to understand the data better. It uses libraries such as pandas, numpy, matplotlib, and seaborn.

Modelling

The modeling section includes training and evaluating different machine learning models such as:

Linear Regression,
Random Forest Regressor,
Decision Tree Regressor,
Gradient Boosting Regressor,
XGBoost Regressor,
LightGBM Regressor