answer is C Consider training a neural network that has a single output using $5$ training samples. The table below shows the computed $$ D i v$/$ w$\_1,1^(3)$ for each of the input samples. Assuming that w$\_1,1^(3)=1,$ a learning rate $\backslash$eta $=0\mathrm{.}3,$ and we are using gradient decent that updates the weights once after processing all training samples. Then the updated value for w$\_1,1^(3)$ is: $($a$)0\mathrm{.}94($b$)0\mathrm{.}70($c$)1\mathrm{.}06$Consider training a neural network that has a single output using $5$ training samples. The

table below shows the computed $\frac{\text{d}\text{e}\text{l}\text{D}\text{i}\text{v}}{del{w}_{1,1}^{(3)}}$ for each of the input samples.

Assuming that $w_{1,1}^{(3)}=1,$ a learning rate $=0\mathrm{.}3,$ and we are using gradient decent that

updates the weights once after processing all training samples. Then the updated value for

$w_{1,1}^{(3)}$ is:

$($a$)0\mathrm{.}94$

$($b$)0\mathrm{.}70$

$($c$)1\mathrm{.}06$

$($d$)1\mathrm{.}30$

$($e$)$ None of the above