Create app.py

app.py

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+import streamlit as st
+import numpy as np
+from sklearn.linear_model import LinearRegression
+
+# Sample training data (Experience vs. Salary)
+data = {
+    "experience": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10],
+    "salary": [30000, 35000, 40000, 45000, 50000, 55000, 60000, 65000, 70000, 75000, 80000]
+}
+
+# Train a simple linear regression model
+X = np.array(data["experience"]).reshape(-1, 1)
+y = np.array(data["salary"])
+model = LinearRegression()
+model.fit(X, y)
+
+# Streamlit app
+def main():
+    st.title("Salary Prediction Application")
+    st.write("This application predicts your salary based on your experience.")
+
+    # Input from user
+    experience = st.number_input("Enter your experience (in years):", min_value=0, max_value=50, value=0, step=1)
+
+    # Predict salary
+    predicted_salary = model.predict([[experience]])[0]
+
+    # Display prediction
+    st.header(f"Predicted Salary: ${predicted_salary:,.2f}")
+
+if __name__ == "__main__":
+    main()