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Question 42 MSQ · 5.0 marks
Consider the two binary images shown below. The white square represents 0 and the black square
represents 1. Suppose we use MP neuron to classify these two images by flattening the image of
size 5 × 5 into a vector of length 25 × 1.
Which of the following threshold θ will help the MP neuron classify these two images correctly with
the following decision rule? Assume the image of number two belongs to class (1) and the image
of number one belongs to class (0)
6406532266596.
10
6406532266597.
9
6406532266598.
11
6406532266599.
14
6406532266600.
16
6406532266601.
None of these
A published solution is not available for this question yet.
Based on the above data, answer the given subquestions.
Suppose we run the model on the single input-output pair (x = 1, y = 0.062) for a few iterations by
randomly initializing w and b. Moreover, the loss value is recorded for each iteration. We observe
that the loss becomes zero after some iterations. This implies that the model has captured the
true value of w and b that generated the pair x, y. The implication is
6406532266606.
TRUE
6406532266607.
FALSE
A published solution is not available for this question yet.
A team has a data set that contains 10000 samples for training a feed-forward neural network.
Suppose they decided to use a mini-batch gradient descent algorithm with a batch size of 100 to
update the weights. How many times do the weights get updated after training the network for 10
epochs?
6406532266624.
1000
6406532266625.
10000
6406532266626.
100000
6406532266627.
10
**Financial Forensics**
**Section Id :** 64065345316
**Section Number :** 4
**Section type :** Online
**Mandatory or Optional :** Mandatory
**Number of Questions :** 12
**Number of Questions to be attempted :** 12
**Section Marks :** 25
**Display Number Panel :** Yes
**Section Negative Marks :** 0
**Group All Questions :** No
**Enable Mark as Answered Mark for Review and**
Yes
**Clear Response :**
**Maximum Instruction Time :** 0
A published solution is not available for this question yet.
