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My bachelors thesis was basically about recommender systems like this. Netflix truly is a sunken ship.
My bachelors thesis was basically about recommender systems like this. Netflix truly is a sunken ship.
It might not stay with the quaint forever.
However I had a lot of fun reading the “Mage Errant” books! It’s a progression Fantasy (comparable genre with shounen anime) that follows a group of students at a magic school as they grow into their powers as they attempt to become strong magic wielders.
I find the book to not only not be bigoted, but be delightfully inclusive in so many aspects, it also includes characters dealing with trauma in a positive way.
I blazed through this 7 book series like popcorn.
Other than that, there are many good suggestions here!
Absolutely loving ours like this. But we also still use a bunch of streaming services occationally
Got Express right before they sold. Going to swap very soon! Mainly looking at proton for the swap
Is that the "network interface"setting? Bit new and clueless to this
It’s not widely available and its only in Norwegian, sadly.
However, I will second @mkengine proposal for Letterboxd, I think it is the superior site to nerd out on. Discovery can be a challenge, depending on your own level of investment into the medium. I’m a big ol movie-nerd, and I’m currently grateful to have access to most streaming services through friends/family/partner so I get to browse them if desired.
Apart from that my twitter algorithm is quite skewed towards movies, and I have a “list” on there (curated users you can browse, kind of like a community on here. That’s been great.
Other than that, I listed to podcast, sometimes check out our national newspapers reviews (but most of those reviewers are already in the aforementioned twitter-list) etc.
As for reading on recommender systems and the algorithm for netflix. My work was based around bias and “trust” when it comes to the recommender systems and how much it recommended/pushed “its own agenda” to users despite having differential tastes.
Good keywords I enjoyed was: recommender system bias I also read some good articles on the spotify recommender systems. But those mostly centered around people growing attached to their algorhitms. It was a fun read.