text_plain_output_1.png image_output_1.png
from tensorflow.keras.layers import Dense,Conv2D, MaxPooling2D, Flatten,BatchNormalization,Dropout

from tensorflow.keras.models import Sequential

model = Sequential()
model.add(Conv2D(32, (3, 3), input_shape=(28, 28, 1), padding='same', activation='relu'))
model.add(BatchNormalization(momentum=0.9, epsilon=1e-05, gamma_initializer='uniform'))
model.add(MaxPooling2D())
model.add(Dropout(0.25))
model.add(Conv2D(64, (3, 3), padding='same', activation='relu'))
model.add(BatchNormalization(momentum=0.9, epsilon=1e-05, gamma_initializer='uniform'))
model.add(MaxPooling2D())
model.add(Dropout(0.25))
model.add(Conv2D(64, (3, 3), padding='same', activation='relu'))
model.add(BatchNormalization(momentum=0.9, epsilon=1e-05, gamma_initializer='uniform'))
model.add(MaxPooling2D())
model.add(Dropout(0.25))
model.add(Flatten())
model.add(Dense(128, activation='relu'))
model.add(Dense(256, activation='relu'))
model.add(Dense(10, activation='sigmoid'))
model.summary()