Neural Network

import tensorflow as tf

keras = tf.keras

embed_size = 50

user_inp = keras.layers.Input(name="user", shape=(1,))
news_inp = keras.layers.Input(name="news", shape=(1,))
user_embed = keras.layers.Embedding(name="user_embed",
                                    input_dim=len(user_id_to_num),
                                    output_dim=embed_size)(user_inp)
news_embed = keras.layers.Embedding(name="news_embed",
                                    input_dim=len(news_id_to_num),
                                    output_dim=embed_size)(news_inp)

# Merge the layers with a dot product along the second axis
merged = keras.layers.Dot(name="merged", normalize=True,
                          axes=2)([user_embed, news_embed])
merged = keras.layers.Reshape(target_shape=(1,))(merged)
out = keras.layers.Dense(1, activation="sigmoid")(merged)
model = keras.Model(inputs=[user_inp, news_inp], outputs=out)
model.compile(optimizer=keras.optimizers.Adam(), loss=keras.losses.mean_squared_error,
              metrics=["accuracy"])