Update app.py

app.py

@@ -8,7 +8,7 @@ import matplotlib.pyplot as plt
 # Streamlit UI
 st.title('Celsius to Fahrenheit Conversion with TensorFlow')
 
-# Define the model with a different weight initializer
+# Define the model
 model = tf.keras.Sequential([
     tf.keras.layers.Dense(units=1, input_shape=[1])
 ])
@@ -39,16 +39,20 @@ if st.button('Train Model and Predict Fahrenheit'):
     # Predictions for visualization
     predictions = model.predict(celsius)
 
-    # Plotting
+    # Plotting Conversion Graph
+    plt.figure(figsize=(8, 4))
     plt.scatter(celsius, fahrenheit, label='Actual Conversion')
     plt.plot(celsius, predictions, color='red', label='Predicted Conversion')
     plt.xlabel('Celsius')
     plt.ylabel('Fahrenheit')
+    plt.title('Celsius to Fahrenheit Conversion')
     plt.legend()
     st.pyplot(plt)
 
+    # Plotting Training Loss Graph
+    plt.figure(figsize=(8, 4))
+    plt.plot(history.history['loss'])
+    plt.title('Model Training Loss')
     plt.xlabel('Epoch Number')
     plt.ylabel("Loss Magnitude")
-    plt.plot(history.history['loss'])
-    plt.legend()
     st.pyplot(plt)