1. 程式人生 > >DEEP & WIDE MODEL

DEEP & WIDE MODEL

轉自:https://www.jianshu.com/p/28a1849f6707

前言:應該只要一天時間,先看Google英文論文,配合中文翻譯:http://d0evi1.com/widedeep-recsys,再看些官方的程式碼,需要先了解下tensorflow的feature API:

tf.contrib.layers 中提供了一系列的函式定義不同型別的 feature columns:
tf.contrib.layers.sparse_column_with_XXX 構建低維離散特徵
sparse_feature_a = sparse_column_with_hash_bucket(…)
sparse_feature_b = sparse_column_with_hash_bucket(…)
tf.contrib.layers.crossed_column 構建離散特徵的組合
sparse_feature_a_x_sparse_feature_b = crossed_column([sparse_feature_a, sparse_feature_b], …)
tf.contrib.layers.real_valued_column 構建連續型實數特徵
real_feature_a = real_valued_column(…)
tf.contrib.layers.embedding_column 構建 embedding 特徵
sparse_feature_a_emb = embedding_column(sparse_id_column=sparse_feature_a, )
feature_column API:

https://github.com/tensorflow/tensorflow/blob/master/tensorflow/python/feature_column/feature_column_lib.py

1)Google 官方資料:

wide and deep論文:
https://arxiv.org/pdf/1606.07792.pdf
wide and depp 主函式:https://github.com/tensorflow/tensorflow/blob/b474e55c23e5cc42b01a1ddea34751f01110deb6/tensorflow/python/estimator/canned/dnn_linear_combined.py


tf.estimator.DNNLinearCombinedClassifier主函式引數:
https://www.w3cschool.cn/tensorflow_python/tensorflow_python-4gn82dty.html
wide_n_deep_tutorial.py程式碼例子:https://github.com/tensorflow/tensorflow/blob/88abddbc30a34855d8cdf44c81eac388fbec955b/tensorflow/examples/learn/wide_n_deep_tutorial.py
wide_and_deep.md:
https://github.com/tensorflow/tensorflow/blob/752dcb61ef7a8fd6555909dc37c1f2a2e5792227/tensorflow/docs_src/tutorials/wide_and_deep.md

TensorFlow Linear Model Tutorial:
https://github.com/tensorflow/tensorflow/blob/752dcb61ef7a8fd6555909dc37c1f2a2e5792227/tensorflow/docs_src/tutorials/wide.md

2)非官網參考資料:

TensorFlow下的大規模線性模型:
http://www.jianshu.com/p/afe41ae17a16
tensorflow邏輯迴歸:http://blog.csdn.net/willduan1/article/details/53105603
tensorlfow線性模型
http://shuaizhang.tech/2016/12/17/Tensorflow-Tutorial-5-Linear-Model-%E7%BA%BF%E6%80%A7%E6%A8%A1%E5%9E%8B/
wide and depp 論文中文翻譯:
基於Wide & Deep Learning的推薦系統http://d0evi1.com/widedeep-recsys/
Summary Of recommender system surveys in recent years:
http://shuaizhang.tech/2017/07/28/Summary-of-Recommender-System-Surveys-in-recent-years/
各大公司廣泛使用的線上學習演算法FTRL詳解:
http://www.cnblogs.com/EE-NovRain/p/3810737.html
Tensorflow - wide and deep.ipynb:
https://github.com/bartgras/XGBoost-Tensorflow-Wide-and-deep-comparison/blob/master/Tensorflow%20-%20wide%20and%20deep.ipynb
TensorFlow Wide And Deep 模型詳解與應用:
http://geek.csdn.net/news/detail/235465
TensorFlow Wide And Deep 模型詳解與應用(二):
http://geek.csdn.net/news/detail/235471
tensorflow線性模型以及Wide deep learning:
http://blog.csdn.net/zhangshuaizaxia/article/details/53707301
TensorFlow 廣度和深度學習教程:
http://www.jianshu.com/p/7dc588d98a94
深度學習在美團點評推薦平臺排序中的應用&& wide&&deep推薦系統模型--學習筆記:
http://www.cnblogs.com/wuxiangli/p/7258474.html
Google_Wide&Deep Learning
http://www.datakit.cn/blog/2016/08/21/wdnn.html