Figure from the original question paper

(A) Option figure from the original question paper

(B) Option figure from the original question paper

(C) Option figure from the original question paper

(D) Option figure from the original question paper

Deep Learning End Term: 3 September 2023, Set QPE1-S1 (May 2023 term)

Question 1

+2 marksOne correct option

Which of the following threshold $\theta$ value of MP neuron implements AND Boolean function denoted by $f(\mathbf{x})$ ? Assume that the number of inputs $x_i$ to the neuron is seven and the neuron does not have any inhibitory inputs.

$f(\mathbf{x}) = \begin{cases} 1, & \text{if } \sum_{i=0}^{6} x_i > \theta \\ 0, & \textit{otherwise} \end{cases}$

A
0
B
-6
C
6
D
7
E
-7

Question 2

+2 marksOne correct option

Consider the statement “the attention mechanism in RNN based Encoder- Decoder architecture helps the decoder to understand the context of words in a given sentence”. The statement is

A
True
B
False

Also asked in End Term 3 Sept 2023

Question 3

+3 marksOne or more correct options

Select all that apply.

14 more questions in this paper

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More on the Deep Learning End Term 3 Sept 2023 Set QPE1-S1 paper

The IIT Madras BS Deep Learning (Deep Learning) End Term paper sat on 3 Sept 2023, in the May 2023 term, set QPE1-S1: 17 questions for 50 marks in 180 minutes. The first 3 questions are below. Sign in with Google — it is free — to see the whole paper with its answers and explanations, in learning mode or as a timed mock test.

Feature	Deep Learning End Term 3 Sept 2023 Set QPE1-S1 at a glance
Term	May 2023 term
Subject	Deep Learning
Course code	BSCS3004
Questions	17
Marks	50
Duration	180 min
MCQ	6
MSQ	3
Numerical	8
Official paper	IIT M DEGREE ET1 EXAM QPE1 S2 03 Sep
Negative marking	No negative marking.
Updated	25 Sept 2026

Other sets that day

Set QPE1-S2