Just stacking layers
def Net():
return tf.keras.models.Sequential([
tf.keras.layers.Conv2D(filters=32, kernel_size=3, activation=tf.keras.activations.relu),
tf.keras.layers.Conv2D(filters=32, kernel_size=3, activation=tf.keras.activations.relu),
tf.keras.layers.Conv2D(filters=32, kernel_size=3, activation=tf.keras.activations.relu),
tf.keras.layers.Conv2D(filters=32, kernel_size=3, activation=tf.keras.activations.relu),
tf.keras.layers.MaxPool2D(pool_size=2, strides=2),
tf.keras.layers.Dropout(0.2),
tf.keras.layers.Conv2D(filters=64, kernel_size=3, activation=tf.keras.activations.relu),
tf.keras.layers.Conv2D(filters=64, kernel_size=3, activation=tf.keras.activations.relu),
tf.keras.layers.Conv2D(filters=64, kernel_size=3, activation=tf.keras.activations.relu),
tf.keras.layers.MaxPool2D(pool_size=2, strides=2),
tf.keras.layers.Dropout(0.2),
tf.keras.layers.Flatten(),
tf.keras.layers.Dense(128, activation=tf.keras.activations.relu),
tf.keras.layers.Dense(128, activation=tf.keras.activations.relu),
tf.keras.layers.Dropout(0.1),
tf.keras.layers.Dense(10, activation=tf.keras.activations.softmax)
])
kaggle (276/1000)
