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学生对 Coursera Project Network 提供的 Music Recommender System Using Pyspark 的评价和反馈

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Nowadays, recommender systems are everywhere. for example, Amazon uses recommender systems to suggest some products that you might be interested in based on the products you've bought earlier. Or Spotify will suggest new tracks based on the songs you use to listen to every day. Most of these recommender systems use some algorithms which are based on Matrix factorization such as NMF( NON NEGATIVE MATRIX FACTORIZATION) or ALS (Alternating Least Square). So in this Project, we are going to use ALS Algorithm to create a Music Recommender system to suggest new tracks to different users based upon the songs they've been listening to. As a very important prerequisite of this course, I suggest you study a little bit about ALS Algorithm because in this course we will not cover any theoretical concepts. Note: This project works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions....

1 - Music Recommender System Using Pyspark 的 5 个评论(共 5 个)

创建者 Mariana L F d A

Dec 22, 2020


Nov 24, 2021

创建者 Li J

Mar 3, 2021

创建者 Garigipati P

Oct 6, 2021

创建者 Leonardo M

Nov 3, 2022