| import streamlit as st | |
| import joblib | |
| import numpy as np | |
| with open("src/Housing_linear","rb") as f: | |
| model = joblib.load(f) | |
| st.title("House price prediction") | |
| sqft_living=st.number_input("Sqft living:",min_value=370.00,max_value=13540.00) | |
| sqft_lot=st.number_input("sqft lot:",min_value=6,max_value=1000000000) | |
| floors=st.number_input("Floors:",min_value=1.000,max_value=3.500) | |
| bedrooms = st.number_input("Bedrooms:",min_value=1,max_value=10) | |
| bathrooms=st.number_input("Bathrooms:",min_value=1,max_value=10) | |
| condition=st.number_input("Condition:",min_value=1.000,max_value=5.000) | |
| if st.button("Estimate"): | |
| st.write("Working") | |
| st.snow() | |
| model_input=np.array([[bedrooms,bathrooms,sqft_living,sqft_lot,condition]]) | |
| prediction= model.predict(model_input) | |
| formatted_pred= round(prediction[0],2) | |
| st.write(f"Your Price:(formatted_pred)") | |