cnn

cnn notes

creating a max pooling layer of 2x2 kernel

max_pool = keras.layers.MaxPool2D(pool_size=2)

tensorflow model for mnist dataset :

model = keras.models.Sequential([
     keras.layers.Conv2D(64, 7, activation="relu", padding="same",
     input_shape=[28, 28, 1]),
     keras.layers.MaxPooling2D(2),
     keras.layers.Conv2D(128, 3, activation="relu", padding="same"),
     keras.layers.Conv2D(128, 3, activation="relu", padding="same"),
     keras.layers.MaxPooling2D(2),
     keras.layers.Conv2D(256, 3, activation="relu", padding="same"),
     keras.layers.Conv2D(256, 3, activation="relu", padding="same"),
     keras.layers.MaxPooling2D(2),
     keras.layers.Flatten(),
     keras.layers.Dense(128, activation="relu"),
     keras.layers.Dropout(0.5),
     keras.layers.Dense(64, activation="relu"),
     keras.layers.Dropout(0.5),
     keras.layers.Dense(10, activation="softmax")
])