Keras: simple example

simple-nn-keras.py

import numpy as np
import tensorflow as tf

data_size = 10

input_size = 28 * 28
hidden1_output = 200
output_size = 1

data = np.random.randn(data_size, input_size)
target = np.random.randn(data_size, output_size)

model = tf.keras.Sequential()
model.add(tf.keras.layers.Dense(hidden1_output, input_shape=(input_size,), activation=tf.nn.relu))
model.add(tf.keras.layers.Dense(output_size))

model.compile(loss=tf.keras.losses.mean_squared_error,
              optimizer=tf.keras.optimizers.SGD(lr=1e-3))

model.fit(data, target, epochs=100, batch_size=data_size)