Re:Why is machine learning ‘hard’?
by amelius on Saturday November 12, 2016 @09:42AM
(#12938011)
> Take this single term from the above sentence: "stochastic gradient algorithms", they represent three key areas: statistics, calculus and CS.
Well most practical problems require knowledge of different disciplines, so this is nothing special.
For instance, building a fluid dynamics solver requires knowledge of: physics, numerical mathematics/differential equations, computer science, computational geometry, and probably a few more.
Well most practical problems require knowledge of different disciplines, so this is nothing special.
For instance, building a fluid dynamics solver requires knowledge of: physics, numerical mathematics/differential equations, computer science, computational geometry, and probably a few more.