| import numpy as np | |
| import keras | |
| random_uniform_data = np.random.uniform(0, 1, (2, 2)) | |
| print (random_uniform_data.shape) | |
| model = keras.Sequential([ | |
| keras.layers.Flatten(input_shape=(28, 28)), | |
| keras.layers.Dense(128, activation='relu'), # Hidden layer with ReLU activation | |
| keras.layers.Dense(64, activation='relu'), # Additional hidden layer | |
| keras.layers.Dense(10, activation='softmax') | |
| ]) | |
| print (model.summary()) |