Mbzuai Entry Exam Sample Questions Info

Briefly explain how backpropagation computes gradients in a neural network. Why is the chain rule essential? Section 5: Python & Coding Logic (10%) Question 13: What is the output of the following?

If ( A ) and ( B ) are square invertible matrices, then ( (A + B)^-1 = A^-1 + B^-1 ). Explain briefly. Section 2: Calculus & Optimization (25%) Question 4: Find the gradient ( \nabla f(x,y) ) of ( f(x,y) = \ln(1 + e^xy) ). Then compute the directional derivative at ( (1,0) ) in the direction of ( (1,1) ). mbzuai entry exam sample questions

Let ( X \sim \mathcalN(0,1) ). Compute ( \mathbbE[e^X] ). (Hint: MGF of normal) Briefly explain how backpropagation computes gradients in a