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import streamlit as st
import tensorflow as tf
# Load your model
model = tf.keras.models.load_model('best_dnn_model.h5')
# Define a function to make predictions
def predict(input_data):
prediction = model.predict(input_data)
return prediction
# Streamlit app
st.title('Bank Churn Prediction')
user_input = st.text_input('Enter your input data')
if st.button('Predict'):
input_data = preprocess_user_input(user_input) # Implementing the function based on preprocessing logic
prediction = predict(input_data)
st.write('Prediction:', prediction)
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