This document discusses TensorFlow Wide & Deep models and their applications. It covers feature columns, model estimators, exporting models for TensorFlow Serving, and tools for working with models. It also provides examples of how Alibaba's food delivery service Ele.me has used machine learning techniques like predicting order times and recommending discounts. The document promotes Google Cloud ML Engine for distributed training and serving models at scale.

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TensorFlow Wide & Deep Model
江骏 - 饿了了么深度学习平台 elearn 作者
Machine Learning GDE (Google Developers Experts)

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结构化数据
Structured Data

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传统⽅方法 XGBoost, Scikit-Learn models
https://github.com/dmlc/xgboost

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传统⽅方法 XGBoost, Scikit-Learn models
http://scikit-learn.org/

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Wide & Deep Model
• Submitted on 2016-06-24
• Jointly train a wide linear model and a deep feed-forward neural network
• Productionized and evaluated the system on Google Play
https://arxiv.org/abs/1606.07792

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Wide & Deep Model
https://www.tensorflow.org/tutorials/wide_and_deep
memorization generalization

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特征列列
Feature Columns

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Feature Columns
连续型（如：身⾼高、体重、历史订单量量）
tf.feature_column.numeric_column

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Feature Columns
⾮非连续型
知道具体类别数量量（如：性别、学历、等级、bool）
tf.feature_column.categorical_column_with_vocabulary_list
不不知道具体类别数量量（如：兴趣爱好，可能类别特别多）
tf.feature_column.categorical_column_with_hash_bucket

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Transformed Feature Columns
Bucketed Columns（如：年年龄段、订餐时间段）
⼈人为划分界线
tf.feature_column.bucketized_column
Crossed Columns（如：商家的⼀一系列列特征）
⼈人为告诉线性模型特征的相关性
tf.feature_column.crossed_column

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模型
Model Estimator

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Model

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Estimator
train
evaluate
predict
export_savedmodel
tensorflow/python/estimator/

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Estimator
https://developers.googleblog.com/2017/12/creating-custom-estimators-in-tensorflow.html

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导出模型/使⽤用模型
TensorFlow Serving

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为 TensorFlow Serving 输出模型

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Model ⼯工具
tensorflow/python/tools/saved_model_cli.py
https://youtu.be/sqYdlSF0BI8?t=30m4s
# What meta_graphs are in a model?
saved_model_cli show --dir /tmp/model_dir
# What signatures are in a meta_graph?
saved_model_cli show --dir /tmp/model_dir --tag_set serve
# What input & output tensors are in a signature?
saved_model_cli show --dir /tmp/model_dir --tag_set serve --signature_def serving_default
# Run a graph
saved_model_cli show --dir /tmp/model_dir --tag_set serve --signature_def xxx --inputs x1=/xxx/
xxx.npy --input_exprs 'x2=np.ones((3,1))'

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Model ⼯工具

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TensorFlow Serving (gRPC)
tensorflow_model_server --port=8500 --model_base_path=xxx
https://www.tensorflow.org/serving/

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a (gRPC) client to call TensorFlow Serving
pip install tensorflow-serving-api
# Build the input data as an Example object
# tf.Example:
# https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/example/example.proto
# tf.Features:
# https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/example/feature.proto
python2.7

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饿了了么实践 & 踩过的坑
ele.me

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饿了了么实践 & 踩过的坑
• 出餐、取餐、送餐 T 时常预估
• 商家到周围区域订单量量预估
• 商家代⾦金金券（红包）发放
• 搜索推荐点击率、购买率预估
• ……

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Google Cloud Machine Learning Engine

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Google CloudML Engine
https://cloud.google.com/ml-engine/
• 分布式训练、弹性伸缩
• 训练任务的监控
• GPU
• Hyperparameter Tuning
• 模型管理理
• 线上 Serving
• 与其它 Google Cloud ⼤大数据系统的整合
• Google Cloud Storage, Google BigQuery, logging, …

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Google CloudML Engine - Model

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I’m 江骏 / ohmystack
@饿了了么
I’m a Machine Learning GDE
(Google Developers Experts)
https://github.com/ohmystack
http://weibo.com/jiangjun1990
http://ohmystack.com/
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dt (docker-tool)
最爽功能：dt ssh 进⼊入 image 或 container
gotool
管理理 Golang 开发环境 GOPATH 的利利器器