Methylation: Neural Network Architecture

neural_net.py

# Basic neural net with 4 dense layers
model = tf.keras.models.Sequential([
    tf.keras.layers.Dense(1024, activation='relu', input_shape=(25,)),
    tf.keras.layers.Dropout(0.2),
    tf.keras.layers.Dense(1024, activation='relu'),
    tf.keras.layers.Dropout(0.2),
    tf.keras.layers.Dense(1024, activation='relu'),
    tf.keras.layers.Dropout(0.2),
    tf.keras.layers.Dense(1)
])

model.compile(loss= "mean_squared_error" , optimizer="adam", metrics=["mean_squared_error"])
model.summary()
model.fit(train_processed_np, train_processed_ages,  epochs=50, validation_data=(test_processed_np, test_processed_ages)