| import model as ml | |
| import streamlit as st | |
| st.title("House Price Prediction") | |
| st.markdown("### Enter the details of the house to get the price prediction") | |
| sqft = st.number_input("Square Feet") | |
| if st.button("Predict"): | |
| price = ml.predict(sqft) | |
| st.success(f"The price of the house will be {price}") | |
| st.divider() | |
| st.subheader("About") | |
| st.write("This is a simple web app to predict the price of the house based on the square feet. I used only 10 data points to train the model. So, the predictions may not be accurate. The model used is Linear Regression. Purpose of this project is to learn how to deploy a machine learning model.") | |
| st.write("Built by [Soham Sagathiya](https://soham901.vercel.app)") | |
| with st.expander("Model Performance"): | |
| data = ml.get_model_details() | |
| st.write(f"Score: {data['score']}") | |
| st.write(f"MSE: {data['mse']}") | |
| st.write(f"Coefficient: {data['coef']}") | |
| st.write(f"Intercept: {data['intercept']}") | |