2020-04-21 11:19:42 -04:00
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---
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id: 5e8f2f13c4cdbe86b5c72d9a
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2020-04-24 05:52:42 -05:00
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title: 'Convolutional Neural Networks: Picking a Pretrained Model'
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2020-04-21 11:19:42 -04:00
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challengeType: 11
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videoId: h1XUt1AgIOI
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2021-01-13 03:31:00 +01:00
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dashedName: convolutional-neural-networks-picking-a-pretrained-model
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2020-04-21 11:19:42 -04:00
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---
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2020-11-27 19:02:05 +01:00
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# --question--
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2020-04-21 11:19:42 -04:00
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2020-11-27 19:02:05 +01:00
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## --text--
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2020-04-21 11:19:42 -04:00
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2020-11-27 19:02:05 +01:00
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Fill in the blanks below to use Google's pre-trained MobileNet V2 model as a base for a convolutional neural network:
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2020-05-28 22:40:36 +09:00
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2020-11-27 19:02:05 +01:00
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```py
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base_model = tf.__A__.applications.__B__(input_shape=(160, 160, 3),
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include_top=__C__,
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weights='imagenet'
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)
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```
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2020-05-28 22:40:36 +09:00
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2020-11-27 19:02:05 +01:00
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## --answers--
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2020-05-28 22:40:36 +09:00
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2020-11-27 19:02:05 +01:00
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A: `keras`
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2020-05-28 22:40:36 +09:00
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2020-11-27 19:02:05 +01:00
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B: `MobileNetV2`
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2020-05-28 22:40:36 +09:00
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2020-11-27 19:02:05 +01:00
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C: `False`
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2020-05-28 22:40:36 +09:00
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2020-11-27 19:02:05 +01:00
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---
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2020-05-28 22:40:36 +09:00
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2020-11-27 19:02:05 +01:00
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A: `Keras`
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2020-05-28 22:40:36 +09:00
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2020-11-27 19:02:05 +01:00
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B: `MobileNetV2`
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C: `True`
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---
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A: `keras`
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B: `mobile_net_v2`
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C: `False`
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## --video-solution--
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2020-04-21 11:19:42 -04:00
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2020-11-27 19:02:05 +01:00
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1
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2020-04-21 11:19:42 -04:00
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