qWhile true, we are not using the same tools as we did in the 50s. Especially with the very quickly evolving situation of today, half measures and hacks are normal.
Hey man, take this data, clean it up and load it in your Linux machine. Do some parameter optimisation and variable selection on a set of different models, among which also include a neural network. Then come back with a strategy to perform sensible model selection and comparison.
You can go back further if you remove the constraint on using Linux.
Tools were there, TBF I have seen MATLAB libraries from back then who were much better than your current scikits and the likes.
ML is a very new field and so most programs are not mature, and indeed they can have you messing around with venvs and such.
But most python software people actually used is packaged by a distro already.
ML has been there since the 1950s. What is an old field for you?
🙄
qWhile true, we are not using the same tools as we did in the 50s. Especially with the very quickly evolving situation of today, half measures and hacks are normal.
We are however using the same tools from the 90s.
Hey man, take this data, clean it up and load it in your Linux machine. Do some parameter optimisation and variable selection on a set of different models, among which also include a neural network. Then come back with a strategy to perform sensible model selection and comparison.
You can go back further if you remove the constraint on using Linux.
Tools were there, TBF I have seen MATLAB libraries from back then who were much better than your current scikits and the likes.