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Showing posts with the label Research and Scholarly Articles

Music Recommendations: Fusion of advanced ML with Musicology and Latent Elements

  It's commonly seen, regardless of the type of content or experience, to use recommendation systems based on User Behavior thanks to the countless algorithms available. The easiest example given to students is usually related to the recommendation systems in shopping platforms like Amazon, where they track what you've previously ordered, what you regularly eyeball, what users like YOU have bought together  your location and calendar holidays that might have impacts on your preferences, and a lot of other data that gets tracked with whatever you may do on their platform (or even off of it). In terms of music, however, giant platforms like Spotify are doing this really well. This is my attempt to see what data insights can be gathered if I would implement algorithms that click for me in this use case, without first analysing what they're using.  Call this a random experiment. Fair warning, the content being discussed is being used for a team project I'm involved in, so m...