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Predicting movie ratings and recommender systems
Arkadiusz Paterek
其他書名
A 195-page monograph on machine learning, recommender systems, and the Netflix Prize.
出版Arkadiusz Paterek, 2012-06-19
主題Mathematics / Probability & Statistics / GeneralMathematics / Probability & Statistics / Bayesian AnalysisMathematics / Probability & Statistics / Regression Analysis
URLhttp://books.google.com.hk/books?id=qbGMpZXWvzoC&hl=&source=gbs_api
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註釋

A 195-page monograph by a top-1% Netflix Prize contestant. Learn about the famous machine learning competition. Improve your machine learning skills. Learn how to build recommender systems.

What's inside:introduction to predictive modeling,a comprehensive summary of the Netflix Prize, the most known machine learning competition, with a $1M prize,detailed description of a top-50 Netflix Prize solution predicting movie ratings,summary of the most important methods published - RMSE's from different papers listed and grouped in one place,detailed analysis of matrix factorizations / regularized SVD,how to interpret the factorization results - new, most informative movie genres,how to adapt the algorithms developed for the Netflix Prize to calculate good quality personalized recommendations,dealing with the cold-start: simple content-based augmentation,description of two rating-based recommender systems,commentary on everything: novel and unique insights, know-how from over 9 years of practicing and analysing predictive modeling.