Machine Learning, Data Science, Ai Programming, Model Performance, Tech Education.
keras.datasets.mnist.load_data() # Normalize pixel values X_train = X_train / 255.0 X_test = X_test / 255.0 # Build the model model = keras.Sequential([ keras.layers.Flatten(input_shape=(28, 28)), keras.layers.Dense(128, activation='relu'), keras.layers.Dense(10, activation='softmax') ]) # Compile