import tensorflow.keras as keras model = keras.Sequential([ keras.layers.Dense(32, input_shape=(784,), activation='relu'), keras.layers.Dense(10, activation='softmax') ])
import tensorflow.keras as keras model = keras.Sequential([ keras.layers.Conv2D(32, (3, 3), activation='relu', input_shape=(28, 28, 1)), keras.layers.MaxPooling2D((2, 2)), keras.layers.Conv2D(64, (3, 3), activation='relu'), keras.layers.MaxPooling2D((2, 2)), keras.layers.Flatten(), keras.layers.Dense(10, activation='softmax') ])This model has two convolutional layers, each followed by a max pooling layer, for feature extraction. The flattened output is then fed into a fully connected layer with a softmax activation function for classification purposes. Package library: TensorFlow