Recommend-master.zip （84个子文件） 
Recommend-master 3_用户建模_1210 
Wide_Deep_Learning_demo.ipynb 110KB README.md 9KB 2_召回算法_1203 .ipynb_checkpoints word2vec-checkpoint.ipynb 353KB
text8.zip 29.89MB word2vec.ipynb 353KB word2vec_homework.ipynb 311KB README.md 9KB image 
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推荐系统实践-3.pdf 5.38MB 1_推荐系统简介_1128 bandits.py 7KB FirstWeek.md 17KB 推荐系统实践-课件.pdf 8.38MB 第一课课件 推荐系统简介 Item-Based Collaborative Filtering Recommendation Algorithms.pdf 252KB Recommending items to more than a billion people - Facebook Code.pdf 822KB Factorization Meets the Neighborhood_ a Multifaceted Collaborative Filtering Model.pdf 281KB Factorization Machines with libFM.pdf 399KB Matrix factorization techniques for recommender systems.pdf 298KB Recommender-Systems-[Netflix].pdf 1.48MB Recommender Systems Handbook.pdf 8.33MB Matrix factorization techniques for recommender systems(1).pdf 298KB Real-time Personalization using Embeddings for Search Ranking at Airbnb.pdf 10.27MB Item-Based Collaborative Filtering Recommendation Algorithms(1).pdf 252KB bandits-注释版.py 3KB 4_重排序算法_1217 README.md 12KB bpr.ipynb 11KB 推荐系统实战-5.pdf 6.98MB test Download.py 3KB master 0B README.md 894B 2_召回算法_1202 .ipynb_checkpoints movie_recommender-Copy1-checkpoint.ipynb 342KB movie_recommender-checkpoint.ipynb 792KB 1543930599354.png 124KB 1543924682455.png 282KB 1543924651403.png 116KB 1543924311138.png 97KB 1543935595599.png 63KB 1543924772249.png 53KB 1543932942930.png 75KB output_104_0.png 23KB 1543926731029.png 81KB 1408.5882.pdf 236KB 1543932633429.png 64KB notebook.tex 391KB 1543929919782.png 76KB 1543925263064.png 12KB 1543935693420.png 29KB 1543924259976.png 173KB README.md 12KB 1543934719076.png 59KB 1543925867719.png 9KB movie_recommender.py 41KB 1543930959628.png 78KB output_106_0.png 35KB 1543935498189.png 268KB 1543935467487.png 64KB movie_recommender.ipynb 795KB 1543924517050.png 64KB 1543924944974.png 16KB .gitignore 34B
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