2020-08-13 12:00:20 +02:00
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---
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id: 5e8f2f13c4cdbe86b5c72d9a
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2021-07-15 13:04:11 +05:30
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title: '卷积神经网络:选择预训练模型'
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2020-08-13 12:00:20 +02:00
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challengeType: 11
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videoId: h1XUt1AgIOI
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2021-10-03 12:24:27 -07:00
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bilibiliIds:
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aid: 463063633
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bvid: BV1qL411x73q
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cid: 409132626
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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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2020-08-13 12:00:20 +02:00
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---
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2020-12-16 00:37:30 -07:00
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# --question--
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2020-08-13 12:00:20 +02:00
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2020-12-16 00:37:30 -07:00
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## --text--
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2020-08-13 12:00:20 +02:00
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2021-07-15 13:04:11 +05:30
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填写下面的空白,使用谷歌预训练的 MobileNet V2 模型作为卷积神经网络的基础:
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2020-08-13 12:00:20 +02:00
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2020-12-16 00:37:30 -07:00
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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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## --answers--
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2020-08-13 12:00:20 +02:00
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2020-12-16 00:37:30 -07:00
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A: `keras`
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2020-08-13 12:00:20 +02:00
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2020-12-16 00:37:30 -07:00
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B: `MobileNetV2`
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2020-08-13 12:00:20 +02:00
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2020-12-16 00:37:30 -07:00
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C: `False`
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2020-08-13 12:00:20 +02:00
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2020-12-16 00:37:30 -07:00
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---
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2020-08-13 12:00:20 +02:00
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2020-12-16 00:37:30 -07:00
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A: `Keras`
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2020-08-13 12:00:20 +02:00
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2020-12-16 00:37:30 -07:00
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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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1
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