If you don't understand how it works your won't understand how to optimize things, how to do error analysis, how to implement better features and weights out of the box, how to choose the right algorithm from the start, how to do good cross validation ...
Yes, you can take a library and implement it in 10 minutes, but then you're really not learning machine learning, are you?
I will argue you do not need four years of math by any stretch, though. The stumbling block will be notation more than anything else. Relatively basic calculus and linear algebra will suffice.
They were right about one thing: the code is the least important part.
Yes, you can take a library and implement it in 10 minutes, but then you're really not learning machine learning, are you?
I will argue you do not need four years of math by any stretch, though. The stumbling block will be notation more than anything else. Relatively basic calculus and linear algebra will suffice.
They were right about one thing: the code is the least important part.