Bayesian Network and Influence Diagrams

#1
Hello everyone,

I started studying Bayesian networks as a self-taught. I am currently struggling with the process of marginalizing out a variable (P(E)) and normalizing with respect to A after computing the joint distribution.
Exercise:
Given data
P (E)= (0.01, 0.99); P(B)=(0.1, 0.9) and the conditional probability table for P(A|B,E) (attached)
  1. perform conditional probability distribution (done);
  2. marginalize out E of P(A,B,E) to obtain P(A,B) (question);
  3. Normalize P(A, B) with respect to A (question)
The exercise has been already done. However, I would like to understand better the calculation.
Thank you in advance
 

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