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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386
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TensorFlow Extended（TFX）的一部分，TFX 是用于在生产环境中部署 TensorFlow 模型
的端到端平台。首先要使用诸如 TF Transform 之类的 TFX 组件，必须先安装它。它没
有与 TensorFlow 捆绑在一起。通过使用 TF Transform 函数进行缩放、存储等操作，你
只需定义一次预处理函数（在 Python 中）。你还可以使用所需的任何 TensorFlow 操作。
如果我们只有两个特征，则此预处理函数如下所示：
import tensorflow_transform as tft
def
preprocess(inputs): #
inputs = a batch of input features
median_age = inputs["housing_median_age"]
ocean_proximity = inputs["ocean_proximity"]
standardized_age = tft.scale_to_z_score(median_age)
ocean_proximity_id = tft.compute_and_apply_vocabulary(ocean_proximity)
return
{
"standardized_median_age": standardized_age,
"ocean_proximity_id": ocean_proximity_id
}
接下来，TF T ...