Update app.py

app.py

@@ -10,15 +10,11 @@ st.title('Celsius to Fahrenheit Conversion with TensorFlow')
 
 # Define the model with a different weight initializer
 model = tf.keras.Sequential([
-    tf.keras.layers.Dense(units=1, input_shape=[1], kernel_initializer='he_normal')
+    tf.keras.layers.Dense(units=1, input_shape=[1])
 ])
 
-# Set a suitable learning rate and number of epochs
-learning_rate = 0.01
-epochs = 500
-
 # Compile the model with the Adam optimizer and loss function
-optimizer = tf.keras.optimizers.Adam(learning_rate=learning_rate)
+optimizer = tf.keras.optimizers.Adam(0.01)
 model.compile(optimizer=optimizer, loss='mse')
 
 # Training data (Celsius to Fahrenheit)
@@ -32,7 +28,7 @@ input_celsius = st.number_input('Enter Celsius value:', value=0.0, format="%.1f"
 if st.button('Train Model and Predict Fahrenheit'):
     with st.spinner('Training...'):
         # Fit the model
-        model.fit(celsius, fahrenheit, epochs=epochs, batch_size=4)
+        model.fit(celsius, fahrenheit, epochs=500)
     st.success('Training completed!')
 
     # Make prediction