2020-08-13 12:00:20 +02:00
|
|
|
---
|
|
|
|
id: 5e8f2f13c4cdbe86b5c72d9a
|
|
|
|
challengeType: 11
|
|
|
|
videoId: h1XUt1AgIOI
|
2021-01-13 03:31:00 +01:00
|
|
|
dashedName: convolutional-neural-networks-picking-a-pretrained-model
|
2020-08-13 12:00:20 +02:00
|
|
|
---
|
|
|
|
|
2020-12-16 00:37:30 -07:00
|
|
|
# --question--
|
2020-08-13 12:00:20 +02:00
|
|
|
|
2020-12-16 00:37:30 -07:00
|
|
|
## --text--
|
2020-08-13 12:00:20 +02:00
|
|
|
|
2020-12-16 00:37:30 -07:00
|
|
|
Fill in the blanks below to use Google's pre-trained MobileNet V2 model as a base for a convolutional neural network:
|
2020-08-13 12:00:20 +02:00
|
|
|
|
2020-12-16 00:37:30 -07:00
|
|
|
```py
|
|
|
|
base_model = tf.__A__.applications.__B__(input_shape=(160, 160, 3),
|
|
|
|
include_top=__C__,
|
|
|
|
weights='imagenet'
|
|
|
|
)
|
|
|
|
```
|
|
|
|
|
|
|
|
## --answers--
|
2020-08-13 12:00:20 +02:00
|
|
|
|
2020-12-16 00:37:30 -07:00
|
|
|
A: `keras`
|
2020-08-13 12:00:20 +02:00
|
|
|
|
2020-12-16 00:37:30 -07:00
|
|
|
B: `MobileNetV2`
|
2020-08-13 12:00:20 +02:00
|
|
|
|
2020-12-16 00:37:30 -07:00
|
|
|
C: `False`
|
2020-08-13 12:00:20 +02:00
|
|
|
|
2020-12-16 00:37:30 -07:00
|
|
|
---
|
2020-08-13 12:00:20 +02:00
|
|
|
|
2020-12-16 00:37:30 -07:00
|
|
|
A: `Keras`
|
2020-08-13 12:00:20 +02:00
|
|
|
|
2020-12-16 00:37:30 -07:00
|
|
|
B: `MobileNetV2`
|
|
|
|
|
|
|
|
C: `True`
|
|
|
|
|
|
|
|
---
|
|
|
|
|
|
|
|
A: `keras`
|
|
|
|
|
|
|
|
B: `mobile_net_v2`
|
|
|
|
|
|
|
|
C: `False`
|
|
|
|
|
|
|
|
## --video-solution--
|
|
|
|
|
|
|
|
1
|
|
|
|
|