>>12142127basically this
>>12142758To expand slightly, ML is broad enough that a single definition (mathematically) doesn't quite exist, but we can define almost all ML as:
1) Defining an objective function (e.g., y = b_0 + x*b_1, where x and y are provided data and b_0/b_1 are unknown)
2) Defining a loss/cost function (e.g.,mean squared error or log-loss)
3)implementing an algorithm that minimizes the loss/cost (e.g., gradient descent)
And boom! You have ML.
>>12143337Also big stats dude here (not my degree, but I publish almost exclusively ML papers) and I 100% agree. You need baby-math knowledge to understand most ML algorithms.
NN are actually the easiest to learn, imo, because they're so simple. You literally need high school math at best. Even when you get into the really crazy architectures, most of it is intuitive/easy on the single-function level.
