論文筆記：Wide & Deep Learning for Recommender Systems
論文提要 本文在推薦方面提出一種wide & deep learning算法，也就是將一個寬的線性模型和一個深度神經網絡一起訓練，通過記憶和泛化（memorization and generalization），爲用戶推薦商品。該算法在Google Play上進行了實驗和評估，結果表明，相比單一的寬線性模型和深度網絡，該算法顯著的提高了App安裝量，具有更好的效果。另外，本文開源了一種基於Tens
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- 1. Wide & Deep Learning for Recommender Systems論文筆記
- 2. 論文筆記 - Wide & Deep Learning for Recommender Systems
- 3. 《Wide & Deep Learning for Recommender Systems》論文總結
- 4. 論文閱讀：《Wide & Deep Learning for Recommender Systems》
- 5. Wide & Deep Learning for Recommender Systems
- 6. Wide &Deep Learning for Recommender Systems
- 7. #Paper Reading# Wide & Deep Learning for Recommender Systems
- 8. Wide & Deep Learning for Recommender Systems 翻譯
- 9. Wide & Deep Learning for Recommender Systems 模型實踐
- 10. Paper Reading:Wide & Deep Learning for Recommender Systems
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相關文章
- 1. Wide & Deep Learning for Recommender Systems論文筆記
- 2. 論文筆記 - Wide & Deep Learning for Recommender Systems
- 3. 《Wide & Deep Learning for Recommender Systems》論文總結
- 4. 論文閱讀：《Wide & Deep Learning for Recommender Systems》
- 5. Wide & Deep Learning for Recommender Systems
- 6. Wide &Deep Learning for Recommender Systems
- 7. #Paper Reading# Wide & Deep Learning for Recommender Systems
- 8. Wide & Deep Learning for Recommender Systems 翻譯
- 9. Wide & Deep Learning for Recommender Systems 模型實踐
- 10. Paper Reading:Wide & Deep Learning for Recommender Systems