covariance matrix and interpretation

matrix multiplication different view

matrix calculus:

scalar value function of scalar

vector, scalar value function of vector

matrix, vector, scalar value function of matrix

derivative, gradient, hessian, as related to calculus 1

evolution of projection onto a vector, onto a subspace, onto an affine space, onto hyperplane -> least square -> variants of least square

alternately -> minimum norm problem (how it is projecting 0 onto the subspace)

PDB Note

w(here) = print stack trace

d(own) = move down a frame

u(p) = move up a frame

b = list all breakpoints

b fileName:55 = set breakpoint in file fileName at line 55

b fileName:my_func

b 55, where a == 6

tbreak = temporary breakpoint = removed when first hit

c(lear) = clear all breakpoints

c fileName:lineNum = clear that line’s breakpoint

enable bnumber

disable bnumber




j(ump) # = jump to that line

unt(il) line#

r(eturn) = until current frame exits

c(ontinue) = until you hit a breakpoint

pdb.set_trace() = your code can break into the pdb