This code sets up a simple web application using Streamlit where users can input various parameters related to a house, and it predicts the price of the house using a pre-trained machine learning model, which is included in app.py We have uploaded a dataset named 'cleaned_data.csv' which is used for training and testing the model.This code performs data preprocessing, model training, evaluation, prediction, and serialization of the trained model. It's essentially a pipeline for predicting house prices based on given features, which is the algo.ipynb file
-Link for the machine learning model
