#Jacobian Matrix
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what's your definition for the "jacobian" here? it seems to me that you are taking the derivative w.r.t. square matrices. This is not uncommon but we never called this jacobian.
So I'm differentiating a matrix with respect to a matrix, where a matrix which is on the numerator side is something related to C is equals to A times B, where both A and B are the matrix product, sorry, where C is a matrix product of A and B. So I'm just differentiating it with respect to B. So is this a Jacobian or not?
C= A*B
dev(C)/dev(B) =
is this a jacobian.??
I don't get what you mean.
ok let me go slow
Making sense also works
A jacobian is usually concerned with derivatives of functions from Rn to Rm
not $\mathcal M_{m\times n}(\bR)\to\bR^k$
Coffey
for those you should look into frechet derivatives.
basically i am trying to understand backword auto grad
so i am facing this situation while evaluation of chain rule where
i am partially derivating a
state (assume it as C)
C = W2*(previous state)
dc/d(previous state)
previous state is w1*(input vec) +bias
matrix calculus makes more sense given the context now
is it clear.?? to you now.??
not really no, idk what you want me to help with but read this wiki page : https://en.wikipedia.org/wiki/Matrix_calculus
In mathematics, matrix calculus is a specialized notation for doing multivariable calculus, especially over spaces of matrices. It collects the various partial derivatives of a single function with respect to many variables, and/or of a multivariate function with respect to a single variable, into vectors and matrices that can be treated as sin...
simply i wana know what actually a jacobian is i am not able to get the correct intuation
A jacobian of a function at some point is the matrix of the linear map that approximates it well enough near that point
usually the denominators of jacobian are conventional vectors, not conventional matrices
i see
this is where i getting stucked
dev(v5)/dev(v4)
so my question is for this same partial derivative is this a jacobian.??
forget what i said previously
@thick imp
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