868 B
868 B
id | title | challengeType | videoId | bilibiliIds | dashedName | ||||||
---|---|---|---|---|---|---|---|---|---|---|---|
5e8f2f13c4cdbe86b5c72d98 | Criando uma rede neural convolucional | 11 | kfv0K8MtkIc |
|
creating-a-convolutional-neural-network |
--question--
--text--
Preencha as lacunas abaixo para completar a arquitetura para uma rede neural convolucional:
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
--video-solution--
3