[prades]

I don't like ML frameworks (Tensorflow, etc...), maybe it's because I haven't tried them. My understanding is that they're like a magic black box: you input some data, you adjust some settings, and you wish for the results to be good. Instead, I've taken a direct approach to the collaborative filtering problem, the difficulty being to correlate a huge amount of data. Some said that only quantum computers would one day be fast enough to solve the recommendation problem, until recently a student demonstrated that it could be solved with classical computers.

https://www.quantamagazine.org/teenager-finds-classical-alte...

This student's algorithm is quite different from mine, but I suppose that my algorithm is yet another example of solving the recommendation problem with classical computers.