Update Google-ML-Crash-Course_MNIST_model.py

Google-ML-Crash-Course_MNIST_model.py

@@ -26,6 +26,31 @@ Softmax	The activation function on the output layer that converts the outputs in
 In summary:
 It's a DNN/MLP: It uses stacked Dense (fully-connected) layers.
 It's not a CNN: It lacks Conv2D and MaxPooling2D layers, and it flattens the image data, discarding the crucial 2D spatial information that CNNs are built to exploit.
+
+Model Summary:
+/usr/local/lib/python3.11/dist-packages/keras/src/layers/core/input_layer.py:27: UserWarning: Argument `input_shape` is deprecated. Use `shape` instead.
+  warnings.warn(
+Model: "sequential_1"
+┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓
+┃ Layer (type)                    ┃ Output Shape           ┃       Param # ┃
+┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩
+│ dense_3 (Dense)                 │ (None, 100)            │        78,500 │
+├─────────────────────────────────┼────────────────────────┼───────────────┤
+│ dense_4 (Dense)                 │ (None, 100)            │        10,100 │
+├─────────────────────────────────┼────────────────────────┼───────────────┤
+│ dropout_1 (Dropout)             │ (None, 100)            │             0 │
+├─────────────────────────────────┼────────────────────────┼───────────────┤
+│ dense_5 (Dense)                 │ (None, 10)             │         1,010 │
+└─────────────────────────────────┴────────────────────────┴───────────────┘
+ Total params: 89,610 (350.04 KB)
+ Trainable params: 89,610 (350.04 KB)
+ Non-trainable params: 0 (0.00 B)
+
+Final accuracy (on validation data): 0.96
+
+Evaluating on test data...
+Accuracy on test data: 0.96
+
 """
 
 import glob