cs3004_2022T3_Q1_AN.pdf cs3004_2022T3_Q1_FN.pdf
Deep Learning · Quiz 1 · Sep 2022
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Questions and published explanations below are available without starting a test. Some questions may not have a published solution yet.
Question 100 MCQ · 0.0 marks
[[IMAGE:5c2e0e7f7271ba88_1_0]]

YES
NO
A published solution is not available for this question yet.
Question 101 MCQ · 3.0 marks
[[IMAGE:5c2e0e7f7271ba88_2_1]]

15
10
2
Insufficient information
A published solution is not available for this question yet.
Question 102 MCQ · 3.0 marks
A team has a dataset that contains 100000 samples for training a feed forward neural network.
Suppose they decided to use the mini-batch gradient descent algorithm to update the weights.
How many times do the weights get updated after training the network for 10 epochs with a mini-
batch size of 1000?
100
1000
100000
10
A published solution is not available for this question yet.
Question 103 MSQ · 3.0 marks
[[IMAGE:5c2e0e7f7271ba88_4_2]]

The updated weight,after one iteration, moves past the minimum at A if the
weight is initialized at point D
The updated weight,after one iteration, moves past the minimum at A if the
weight is initialized at point C
The updated weight,after one iteration, moves towards the minimum at A if
the weight is initialized at point C
The updated weight,after one iteration, moves away from the minimum at B if
the weight is initialized at point D
A published solution is not available for this question yet.
Question 104 MCQ · 1.0 marks
[[IMAGE:5c2e0e7f7271ba88_5_3]]
Based on the above data, answer the given subquestions.
Are the data points linearly separable?

Yes
No
A published solution is not available for this question yet.
Question 105 MCQ · 3.0 marks
[[IMAGE:5c2e0e7f7271ba88_5_3]]
Based on the above data, answer the given subquestions.
Suppose that we initialize the weights w of perceptron randomly and run the perceptron learning
algorithm for t iterations. For each iteration, it considers one data point and updates the weights,
if required. The weight after t iterations is shown as w\(^{t}\) in the figure. The algorithm now starts
iterating over the data points in the following order:(D,E,C). What will be the value of w\(^{t}\) after one
more iteration, i.e., what will be the value of w\(^{t+1}\)?

[[IMAGE:5c2e0e7f7271ba88_6_4]]

[[IMAGE:5c2e0e7f7271ba88_6_5]]

[[IMAGE:5c2e0e7f7271ba88_6_6]]

[[IMAGE:5c2e0e7f7271ba88_6_7]]

A published solution is not available for this question yet.
Question 106 MCQ · 3.0 marks
[[IMAGE:5c2e0e7f7271ba88_5_3]]
Based on the above data, answer the given subquestions.
What will be the value of w\(^{t}\) after two more iteration, i.e., what will be the value of w\(^{t+2}\)?

[[IMAGE:5c2e0e7f7271ba88_6_8]]

[[IMAGE:5c2e0e7f7271ba88_6_9]]

[[IMAGE:5c2e0e7f7271ba88_6_10]]

[[IMAGE:5c2e0e7f7271ba88_7_11]]

A published solution is not available for this question yet.
Question 107 MCQ · 3.0 marks
[[IMAGE:5c2e0e7f7271ba88_5_3]]
Based on the above data, answer the given subquestions.
[[IMAGE:5c2e0e7f7271ba88_7_12]]


[[IMAGE:5c2e0e7f7271ba88_7_13]]

[[IMAGE:5c2e0e7f7271ba88_7_14]]

[[IMAGE:5c2e0e7f7271ba88_7_15]]

[[IMAGE:5c2e0e7f7271ba88_7_16]]

A published solution is not available for this question yet.
Question 108 MSQ · 6.0 marks
[[IMAGE:5c2e0e7f7271ba88_8_17]]
Based on the above data, answer the given subquestions.
[[IMAGE:5c2e0e7f7271ba88_9_18]]


[[IMAGE:5c2e0e7f7271ba88_9_19]]

[[IMAGE:5c2e0e7f7271ba88_9_20]]

[[IMAGE:5c2e0e7f7271ba88_9_21]]

[[IMAGE:5c2e0e7f7271ba88_9_22]]

[[IMAGE:5c2e0e7f7271ba88_9_23]]

[[IMAGE:5c2e0e7f7271ba88_10_24]]

A published solution is not available for this question yet.
Question 109 MCQ · 6.0 marks
[[IMAGE:5c2e0e7f7271ba88_8_17]]
Based on the above data, answer the given subquestions.
[[IMAGE:5c2e0e7f7271ba88_10_25]]


TRUE
FALSE
Not possible to decide
A published solution is not available for this question yet.
Question 110 MCQ · 3.0 marks
[[IMAGE:5c2e0e7f7271ba88_8_17]]
Based on the above data, answer the given subquestions.
[[IMAGE:5c2e0e7f7271ba88_11_26]]


[[IMAGE:5c2e0e7f7271ba88_11_27]]

[[IMAGE:5c2e0e7f7271ba88_11_28]]

[[IMAGE:5c2e0e7f7271ba88_11_29]]

[[IMAGE:5c2e0e7f7271ba88_11_30]]

A published solution is not available for this question yet.
Question 111 MSQ · 3.0 marks
[[IMAGE:5c2e0e7f7271ba88_12_31]]
Based on the above data, answer the given subquestions.
Choose the vector(s) that is (are) inappropriate given the network

[[IMAGE:5c2e0e7f7271ba88_12_32]]

[[IMAGE:5c2e0e7f7271ba88_12_33]]

[[IMAGE:5c2e0e7f7271ba88_12_34]]

[[IMAGE:5c2e0e7f7271ba88_13_35]]

A published solution is not available for this question yet.
Question 112 NAT · 4.0 marks
[[IMAGE:5c2e0e7f7271ba88_12_31]]
Based on the above data, answer the given subquestions.
[[IMAGE:5c2e0e7f7271ba88_13_36]]


A published solution is not available for this question yet.
Question 113 MCQ · 3.0 marks
[[IMAGE:5c2e0e7f7271ba88_12_31]]
Based on the above data, answer the given subquestions.
[[IMAGE:5c2e0e7f7271ba88_14_37]]


[[IMAGE:5c2e0e7f7271ba88_14_38]]

[[IMAGE:5c2e0e7f7271ba88_14_39]]

[[IMAGE:5c2e0e7f7271ba88_14_40]]

[[IMAGE:5c2e0e7f7271ba88_14_41]]

A published solution is not available for this question yet.
Question 114 NAT · 3.0 marks
[[IMAGE:5c2e0e7f7271ba88_12_31]]
Based on the above data, answer the given subquestions.
[[IMAGE:5c2e0e7f7271ba88_14_42]]


A published solution is not available for this question yet.
Question 115 MCQ · 3.0 marks
[[IMAGE:5c2e0e7f7271ba88_12_31]]
Based on the above data, answer the given subquestions.
[[IMAGE:5c2e0e7f7271ba88_15_43]]


1.85
-1.85
1.72
-1.72
A published solution is not available for this question yet.