text_plain_output_1.png
import tensorflow as tf

model = tf.keras.Sequential()
model.add(tf.keras.layers.Input(30))
model.add(tf.keras.layers.Dense(512, activation='relu'))
model.add(tf.keras.layers.Dense(256, activation='relu'))
model.add(tf.keras.layers.Dense(128, activation='relu'))
model.add(tf.keras.layers.Dense(1, activation='sigmoid'))
model.compile(optimizer=tf.keras.optimizers.Adam(learning_rate=0.0002), loss='binary_crossentropy', metrics=['accuracy', tf.keras.metrics.TruePositives(), tf.keras.metrics.FalsePositives(), tf.keras.metrics.TrueNegatives(), tf.keras.metrics.FalseNegatives()])
model.summary()