October 2020
Intermediate to advanced
693 pages
16h 26m
Chinese
Content preview from 机器学习实战：基于Scikit-Learn、Keras 和TensorFlow （原书第2 版）
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kera s.layers.Conv2D(32, kernel_size=3, padding="same", activation="selu"),
keras.layers.MaxPool2D(pool_size=2),
kera s.layers.Conv2D(64, kernel_size=3, padding="same",activation="selu"),
keras.layers.MaxPool2D(pool_size=2)
])
conv_decoder = keras.models.Sequential([
keras.layers.Conv2DTranspose(32, kernel_size=3, strides=2, padding="valid",
activation="selu",
input_shape=[3, 3, 64]),
kera s.layers.Conv2DTranspose(16, kernel_size=3, strides=2, padding="same",
activation="selu"),
kera s.layers.Conv2DTranspose(1, kernel_size=3, strides=2, padding ="same",
activation="sigmoid"),
keras.layers.Reshape([28, 28])
])
conv_ae ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.