936 B
936 B
id, title, challengeType, videoId
id | title | challengeType | videoId |
---|---|---|---|
5e8f2f13c4cdbe86b5c72d98 | Creating a Convolutional Neural Network | 11 | kfv0K8MtkIc |
Description
Tests
question:
text: |
Fill in the blanks below to complete the architecture for a convolutional neural network:
```py
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`
solution: 3