1 hidden layer: 100 nodes

We start analazying 100 nodes in the hidden layer.

model.append(tf.keras.models.Sequential([
    tf.keras.layers.Dense(100, kernel_regularizer=tf.keras.regularizers.l2(0.01),
                          activation='relu', input_shape=(784,), name='hidden_1_layer'),
    tf.keras.layers.Dense(10, activation='softmax', name='output_layer')
]))

nn_compile(model[-1], params[3])

model[-1].summary()

Model: "sequential_18"
_________________________________________________________________
 Layer (type)                Output Shape              Param #   
=================================================================
 hidden_1_layer (Dense)      (None, 100)               78500     
                                                                 
 output_layer (Dense)        (None, 10)                1010      
                                                                 
=================================================================
Total params: 79,510
Trainable params: 79,510
Non-trainable params: 0
_________________________________________________________________

tf.keras.utils.plot_model(model[-1], show_shapes=True, show_layer_names=True)