Quiz Space

Deep Learning · Quiz 1 · 26 Oct 2025 · September 2025 term · Set 3

Question 19: After one iteration of gradient descent, will the new we…

Question 19

+2 marksOne correct option

Suppose you build a neural network with one hidden layer that uses sigmoid as an activation function and an output layer with a softmax activation function. You initialize the hidden layer weights W1 randomly and set the output layer weights W2 to all zeros. Assume the bias is set to be zero. You train the network using stochastic gradient descent. Based on the above data, answer the given subquestions.

After one iteration of gradient descent, will the new weight for W2 be the same as the previous weight?

  1. A

    Yes

  2. B

    No

Show answer

Correct answer

  • B

    No

See the whole paperTake it as a mock test

Question 19 of 22 in the IIT Madras BS Deep Learning (Deep Learning) Quiz 1 paper sat on 26 Oct 2025, in the September 2025 term (IIT M DEGREE AN EXAM QDB4 26 Oct 2025). It carries 2 marks.

This question was also asked in

More questions from this paper

  1. Q1THIS IS QUESTION PAPER FOR THE SUBJECT "DEGREE LEVEL : DEEP LEARNING (COMPUTER BASED EXAM)" ARE YOU SURE YOU HAVE TO WR…
  2. Q2Figure question
  3. Q3Figure question
  4. Q4Which of the following statements best describes the primary representational advantage of a Multi-Layer Perceptron (ML…
  5. Q5A data scientist is training a deep learning model on a massive dataset containing billions of data points. They find t…
  6. Q6Figure question
  7. Q7You are adapting a neural network that was originally designed for a 10-class image classification problem to perform a…
  8. Q8Figure question
  9. Q9Figure question
  10. Q10What is the value of the output of the hidden layer? (Answer correct upto two digits after the decimal)
  11. Q11What is the value of the cross entropy loss? (use natural log). (Answer correct upto two digits after the decimal)
  12. Q12Based on the above data, answer the given subquestions.
  13. Q13Use cross entropy loss and compute the gradient of W1 which is the weight between input and hidden layer. (consider upt…
  14. Q14Based on the above data, answer the given subquestions.
  15. Q15Based on the above data, answer the given subquestions.
  16. Q16Based on the above data, answer the given subquestions.
  17. Q17Based on the above data, answer the given subquestions.
  18. Q18After one iteration of gradient descent, will the new weight for W1 be the same as the previous weight?
  19. Q20Based on the above data, answer the given subquestions.
  20. Q21Based on the above data, answer the given subquestions.
  21. Q22Suppose you build a neural network with one hidden layer that uses sigmoid as an activation function and an output laye…