tas (11:37:55)
case*

tas (11:37:49)
basics*

tas (11:37:44)
it's why it's better to start with such asics in cae of ML

tas (11:36:55)
to get better precision, recall etc

tas (11:36:22)
you have to understand what is going there under the hood and how to calculate all the metrics to make decisions what to change

tas (11:35:56)
but without that knowledge it's almost impossible to get good results

tas (11:35:37)
of course you can just learn how to use some algorithms in practice

epso (11:34:55)
it's been since highschool since I really did something with math

tas (11:34:46)
the real hardcore is when you have to come up with the partial derivatives for convolutional neural networks

epso (11:33:52)
I'm lazy and just want to know how to calculate it with something

Congas Parties

Chrylian (Cyril Jegot)

djrandom

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