Netflix's Metaflow: Reproducible machine learning pipelines

Re:Netflix's Metaflow: Reproducible machine learning pipelines by toxik on Monday December 21, 2020 @04:33PM (#25499852)

The basic problem is understanding WHY I liked something. If I watch Tintin because it’s a cozy throwback to my childhood, that does not mean I would like every single Studio Ghibli movie in my recommendations.

Similarly, if I play Blacklist in the background as basically noise, I don’t want to see a bunch of related shows. I guess I could give it a thumbs down but I only do that for actually terrible movies.

Also Spotify and Apple music seem to have okay recommendations

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Re:Netflix's Metaflow: Reproducible machine learning pipelines by kyawzazaw on Monday December 21, 2020 @04:45PM (#25499990)

Music is different from movies and television though. There are beats and rhythms that are easy to identify, lyrics easy to analyze and artists that are roughly categorized.

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Re:Netflix's Metaflow: Reproducible machine learning pipelines by toxik on Monday December 21, 2020 @05:40PM (#25500543)

I feel like that’s not true, music is hard to analyze. Movies have synopses, and are generally categorized by their cast alone. I could figure out LotR belongs together from these datapoints, easily. Not to mention the fact that people watch trilogies in sequence like 99% of the time.

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