--questions--

--text--

Fill in the blanks below to complete the architecture for a convolutional neural network:

model = models.__A__()
model.add(layers.__B__(32, (3, 3), activation='relu', input_shape=(32, 32, 3)))
model.add(layers.__C__(2, 2))
model.add(layers.__B__(64, (3, 3), activation='relu'))
model.add(layers.__C__(2, 2))
model.add(layers.__B__(32, (3, 3), activation='relu'))
model.add(layers.__C__(2, 2))

--answers--

A: Sequential

B: add

C: Wrapper

A: keras

B: Cropping2D

C: AlphaDropout

A: Sequential

B: Conv2D

C: MaxPooling2D

Creating a Convolutional Neural Network

--questions--

--text--

--answers--

--video-solution--