image_output_5.png image_output_7.png image_output_4.png image_output_8.png image_output_6.png image_output_3.png image_output_2.png image_output_1.png
from tensorflow.keras.layers import Dense, Dropout

from tensorflow.keras.models import Sequential

from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense, Dropout
nn_model = Sequential()
nn_model.add(Dense(20, activation='relu', input_shape=(20,)))
nn_model.add(Dropout(0.3, noise_shape=None, seed=None))
nn_model.add(Dense(64, activation='relu'))
nn_model.add(Dense(32, activation='relu'))
nn_model.add(Dropout(0.2, noise_shape=None, seed=None))
nn_model.add(Dense(16, activation='relu'))
nn_model.add(Dropout(0.3, noise_shape=None, seed=None))
nn_model.add(Dense(1, activation='sigmoid'))
nn_model.summary()
nn_model.compile(optimizer='adam', loss='binary_crossentropy', metrics=['accuracy'])