RecoSys:推荐系统学习资源和学习笔记
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2021-03-11
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RecoSys:推荐系统学习资源和学习笔记 （132个子文件） 
ratings.csv 2.27MB movies.csv 473KB train.csv 420KB train.csv 420KB train_set.csv 347KB links.csv 184KB tags.csv 112KB test.csv 108KB test.csv 104KB test.csv 104KB val_set.csv 86KB ratings.dat 23.45MB ratings.dat 23.45MB movies.dat 167KB movies.dat 167KB users.dat 131KB users.dat 131KB Deep_CrossingModel.ipynb 88KB 协同过滤.ipynb 71KB GBDT+LR.ipynb 55KB ItemCF-checkpoint.ipynb 34KB UserCF.ipynb 34KB ItemCF.ipynb 33KB RecommendExample_GuessScore.ipynb 20KB DataLoadAndPreprocessing.ipynb 9KB UserCF-checkpoint.ipynb 1KB RecommendExample_GuessScore-checkpoint.ipynb 72B settings.json 47B settings.json 47B settings.json 47B 推荐系统系列合集.md 574KB 推荐系统遇上深度学习系列二.md 205KB GBDT.md 17KB Wide&Deep模型.md 15KB 推荐系统实践(1)-- 一个好的推荐系统.md 15KB 局部敏感哈希：在常数时间内搜索Embedding最近邻.md 14KB Spark与特征处理.md 14KB 评估指标.md 13KB 基于Embedding+MLP的Deep Crossing.md 12KB README.md 12KB GBDT + LR.md 11KB README.md 11KB Graph Embedding .md 11KB Embedding基础.md 11KB 推荐系统实践(2)--利用用户行为数据进行推荐.md 11KB 评估体系.md 11KB 特征工程.md 10KB 召回层初识.md 10KB NeuralCF.md 10KB 基于Attention的推荐系统-DIN和DIEN.md 9KB 离线评估方法.md 9KB 线上服务及存储模块.md 9KB Neural CF-2017.md 9KB DeepFM.md 9KB 推荐系统实践(5)-利用上下文信息进行推荐.md 9KB 协同过滤和矩阵分解.md 7KB 推荐系统实践(3)--冷启动问题.md 7KB Deep Crossing-2016.md 7KB 线上A:B测试.md 6KB 推荐系统实践(4)--利用标签数据进行推荐.md 6KB YouTube 推荐系统架构.md 5KB 传统推荐模型的特点总结.md 4KB AutoRec-2015.md 4KB 自动特征交叉_FM-FFM.md 4KB README.md 3KB 推荐系统实践(6)--利用社交网络推荐.md 3KB 逻辑回归用于推荐系统.md 2KB README.md 2KB README.md 1KB ml-1m.test.negative 2.75MB
[Recsys Intro slides] Recommender Systems An introduction.pdf 7.62MB [Earliest CF] Using Collaborative Filtering to Weave an Information Tapestry.pdf 1.74MB [MF] Matrix Factorization Techniques for Recommender Systems.pdf 1.48MB [Item2Vec] Item2Vec-Neural Item Embedding for Collaborative Filtering.pdf 1007KB [Word2Vec] Word2vec Parameter Learning Explained.pdf 798KB [FNN] Deep Learning over Multi-field Categorical Data.pdf 570KB [CF] Amazon Recommendations Item-to-Item Collaborative Filtering.pdf 359KB [AutoRec]-2015.pdf 273KB [DCN] Deep & Cross Network for Ad Click Predictions.pdf 256KB [Word2Vec] Distributed Representations of Words and Phrases and their Compositionality.pdf 109KB [Recsys Intro] Recommender Systems Handbook.pdf 19.26MB [Airbnb Embedding] Real-time Personalization using Embeddings for Search Ranking at Airbnb (Airbnb 2018).pdf 9.74MB [NFM] Neural Factorization Machines for Sparse Predictive Analytics.pdf 3.49MB [AFM] Attentional Factorization Machines - Learning the Weight of Feature Interactions via Attention Networks.pdf 3.42MB [NCF] Neural Collaborative Filtering.pdf 1.47MB [DeepFM] A Factorization-Machine based Neural Network for CTR Prediction.pdf 1.2MB [Bilinear] Personalized Recommendation on Dynamic Content Using Predictive Bilinear Models.pdf 1.08MB [GBDT+LR]Practical Lessons from Predicting Clicks on Ads at Facebook 2014.PDF 774KB [Wide&Deep] Wide & Deep Learning for Recommender Systems.pdf 501KB [PNN] Product-based Neural Networks for User Response Prediction.pdf 470KB [Deep Crossing] Deep Crossing - Web-Scale Modeling without Manually Crafted Combinatorial Features.pdf 434KB [ItemCF] Item-Based Collaborative Filtering Recommendation Algorithms.pdf 253KB [Word2Vec] Efficient Estimation of Word Representations in Vector Space.pdf 223KB [FM]Factorization Machines2010.pdf 189KB net_parameter.pkl 1.51MB
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