SalarypPred / 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()