Who does that algorithm really serve?

From the sounds of it: no one, it's just bad. Teachers are passed over for jobs that they should be getting, schools are having difficulty filling teaching roles (and are probably paying extra for temporary teachers), and students are being instructed poorly by a revolving door of poorly qualified teachers. This isn't a zero-sum scenario; getting the right teachers into the right jobs makes everyone happier.

great work! just a note regarding tf-idf, when you mention log10: i think you're missing the point on the reason of log and most importantly base 10. namely, using log10 gives us a perspective on the number of digits of the term/document frequency. if a term "A" occurs 23 times and a term "B" occurs 50, they will have a very close representation (because both numbers are 2 digits ones).

anyway, thanks for the submission

> for index, item in enumerate(menu):

should be

> for index, item in enumerate(menu, start=1):

for the example to be correct :)

you're right, thanks!

yes, i see this as well. at first it was confusing, but later i understood it was the output.

My understanding is that the neural network is used to predict the "magnitude" of each eigenvector/axe (extracted by using PCA) in order to reconstruct an approximation of the original behavior.