@SaiT wrote:
Suppose you have inputs as x, y, and z with values -2, 5, and -4 respectively. You have a neuron ‘q’ and neuron ‘f’ with functions:
q = x + y
f = q * z
Graphical representation of the functions is as follows:
What is the gradient of F with respect to x, y, and z?
(HINT: To calculate gradient, you must find (df/dx), (df/dy) and (df/dz))
A. (-3,4,4)
B. (4,4,3)
C. (-4,-4,3)
D. (3,-4,-4)
A neural network can be considered as multiple simple equations stacked together. Suppose we want to replicate the function for the below mentioned decision boundary.
Using two simple inputs h1 and h2
What will be the final equation?
A. (h1 AND NOT h2) OR (NOT h1 AND h2)
B. (h1 OR NOT h2) AND (NOT h1 OR h2)
C. (h1 AND h2) OR (h1 OR h2)
D. None of these
I am somehow not able to show the figures here use below link
Question no 7 and 09
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