Book Recommendation Engine using KNN

https://www.freecodecamp.org/learn/machine-learning-with-python/machine-learning-with-python-projects/book-recommendation-engine-using-knn

In this challenge, you will create a book recommendation algorithm using K-Nearest Neighbors. You will use the Book-Crossings dataset. This dataset contains 1.1 million ratings (scale of 1-10) of 270,000 books by 90,000 users. You can access the full project instructions and starter code on Google Colaboratory.

https://www.cnblogs.com/beyondChan/p/10861045.html

https://www.cnblogs.com/feily/p/14397470.html

Unsupervised learner for implementing neighbor searches. Read more in the User Guide.

https://datascienceplus.com/building-a-book-recommender-system-the-basics-knn-and-matrix-factorization/

使用 pivot 建立二維虛拟視圖。

https://zhuanlan.zhihu.com/p/29903232

https://github.com/BUVANEASH/Book-Recommendation---Collaborative-Filtering

https://github.com/jalajthanaki/Book_recommendation_system/blob/master/KNN_based_recommendation_system.ipynb

出處：http://www.cnblogs.com/lightsong/

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