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Neural Networks and GANs Quiz

Authored by Mahipal Jadeja

English

University

Used 1+ times

Neural Networks and GANs Quiz
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20 questions

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1.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

The tanh activation usually works better than sigmoid activation function for hidden units because the mean of its output is closer to zero, and so it centers the data better for the next layer. True/False?

True

False

2.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

You are building a binary classifier for recognizing cucumbers (y=1) vs. watermelons (y=0). Which one of these activation functions would you recommend using for the output layer?

ReLU

Leaky ReLU

sigmoid

tanh

3.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

The weights of a neural network should be initialized randomly rather than to all zeros, because if you initialize to all zeros, then the network will fail to break symmetry and will not converge, True/False?

True

False

4.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Derivative of sigmoid activation function is: f(x) = 1/(1+e-x)

f(x) (1-f(x))

f(x) (1+f(x))

f(x) ln(1-f(x))

f(x) ln(1+f(x))

5.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

A binary classifier predicts "Positive" for 80 samples. Out of those, 60 are actually Positive. What is the number of True Positives (TP)?

60

20

80

40

6.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

A classifier predicted 100 negatives, out of which 90 are actually negative. What is the number of True Negatives (TN)?

10

90

100

110

7.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is true about the F1-score?

It is geometric mean of precision and recall

It is arithmatic mean of precision and recall

It is harmonic mean of precision and recall

The relationship can't be established

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