text_plain_output_2.png text_plain_output_1.png
import tensorflow as tf

import tensorflow as tf

modl = tf.keras.Sequential()
modl.add(tf.keras.layers.InputLayer(input_shape=(1, 28, 28, 3)))
modl.add(tf.keras.layers.Conv2D(32, (3, 3), activation='relu'))
modl.add(tf.keras.layers.Flatten())
modl.add(tf.keras.layers.Dense(units=64, activation='relu'))
modl.add(tf.keras.layers.Dense(32, activation='relu'))
modl.add(tf.keras.layers.Dense(4, activation='softmax'))
modl.summary()
optm = tf.keras.optimizers.Adam(learning_rate=0.001)
modl.compile(loss='categorical_crossentropy', optimizer=optm, metrics='accuracy')