Create app.py

app.py

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+import gradio as gr
+import pandas as pd
+import numpy as np
+from sklearn.linear_model import LinearRegression
+
+# Load dataset (online use kar rahe hain taake HF pe chale)
+url = "https://raw.githubusercontent.com/ageron/handson-ml/master/datasets/housing/housing.csv"
+df = pd.read_csv(url)
+
+# Select features
+df = df[['total_rooms', 'households', 'population', 'total_bedrooms']].dropna()
+
+# Split data
+X = df[['total_rooms', 'households', 'population']]
+y = df['total_bedrooms']
+
+# Train model
+model = LinearRegression()
+model.fit(X, y)
+
+# Prediction function
+def predict(total_rooms, households, population):
+    data = np.array([[total_rooms, households, population]])
+    prediction = model.predict(data)[0]
+    return float(prediction)
+
+# Gradio UI
+interface = gr.Interface(
+    fn=predict,
+    inputs=[
+        gr.Number(label="Total Rooms"),
+        gr.Number(label="Households"),
+        gr.Number(label="Population")
+    ],
+    outputs=gr.Number(label="Predicted Bedrooms"),
+    title="Housing Bedrooms Prediction",
+    description="Predict total bedrooms using linear regression"
+)