How neural networks became a universal function approximators?

0 Answers  

---

 Which of the following is not the promise of artificial neural network? a) It can explain result b) It can survive the failure of some nodes c) It has inherent parallelism d) It can handle noise

1 Answers  

---

Which is the similar operation performed by the drop-out in neural network?

0 Answers  

---

What are combination, activation, error, and objective functions?

0 Answers  

---

Having multiple perceptrons can actually solve the XOR problem satisfactorily: this is because each perceptron can partition off a linear part of the space itself, and they can then combine their results. a) True – this works always, and these multiple perceptrons learn to classify even complex problems. b) False – perceptrons are mathematically incapable of solving linearly inseparable functions, no matter what you do c) True – perceptrons can do this but are unable to learn to do it – they have to be explicitly hand-coded d) False – just having a single perceptron is enough

1 Answers  

---

How are artificial neural networks different from normal computers?

0 Answers  

---

The network that involves backward links from output to the input and hidden layers is called as ____. a) Self organizing maps b) Perceptrons c) Recurrent neural network d) Multi layered perceptron

1 Answers  

---

The name for the function in question 16 is a) Step function b) Heaviside function c) Logistic function d) Perceptron function

1 Answers  

---

 Which of the following is true? (i) On average, neural networks have higher computational rates than conventional computers. (ii) Neural networks learn by example. (iii) Neural networks mimic the way the human brain works. a) All of the mentioned are true b) (ii) and (iii) are true c) (i), (ii) and (iii) are true d) None of the mentioned

1 Answers  

---

What is Pooling in CNN and how does it work?

0 Answers  

---

What can you do with an nn and what not?

0 Answers  

---

A perceptron adds up all the weighted inputs it receives, and if it exceeds a certain value, it outputs a 1, otherwise it just outputs a 0. a) True b) False c) Sometimes – it can also output intermediate values as well d) Can’t say

1 Answers  

---