![]() ![]() ![]() Constructive feedback is welcome aggressive complaining is not.ħ. Posts and comments that are needlessly negative or hostile toward Apple Music may be removed. No needlessly negative or hostile posts No aggressive complaining. No self-promotion and advertisements No posts/comments that are advertisements or self-promoting.Ħ. Have integrity No posts/comments about piracy, account sharing, VPN use, etc.ĥ. ![]() No low-quality content Low quality content will be removed without warning.Ĥ. No rude, offensive, or hateful posts/comments.ģ. ![]() If you would like to share a playlist, do so over at r/AppleMusicPlaylistsĢ. They will be removed and you may be banned. Do not post any links to playlists Do not post any links to playlists. If many users like the same songs, the system identifies the songs as similar.R/AppleMusic is a subreddit for discussion of Apple's music streaming service, Apple Music. Instead of clustering similar users, it focuses on the relationships between items. This process, known as user-user collaborative filtering, groups users with similar behavior or preferences.Īnother approach is item-item collaborative filtering. Collaborative filtering takes note of this pattern, and if another user loves listening to Davido but hasn't discovered Wizkid, the system might recommend Wizkid.Ĭollaborative filtering goes a step further by clustering users with similar music interests. If you're a Davido fan and you enjoy listening to Wizkid. The system then uses an algorithm to find the 'K' closest song vectors for every user vector, making recommendations based on these findings. The matrix is transformed into two matrices, the preference matrix and the confidence matrix, which indicates whether a user has listened to a song and how certain the system is about this preference. Collaborative filtering is a process of matrix manipulation, where user-song play counts are organized into a sparse matrix. ![]()
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