Which of the following activation functions can lead to vanishing gradients?

ATI quiz

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Computers
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University
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Easy
Tuấn Nguyễn
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100 questions
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1.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
ReLU
Tanh
Leaky ReLU
None of the above
2.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Which of the following is true about Batchnorm?
Batchnorm is another way of performing dropout
Batchnorm makes training faster
In Batchnorm, the mean is computed over the features
Batchnorm is a non-linear transformation to center the dataset around the origin
3.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
When should multi-task learning be used?
When your problem involves more than one class label
When two tasks have the same dataset
When you have a small amount of data for a particular task that would benefit from the large dataset of another task
When the tasks have datasets of different formats (text and images).
4.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is Error Analysis?
The process of analyzing the performance of a model through metrics such as precision, recall or F1-score.
The process of scanning mis-classified examples to identify weaknesses of a model
The process of tuning hyperparameters to reduce the loss function during training
The process of identifying which parts of your model contributed to the error
5.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Which of the following is a non-iterative method to generate adversarial examples?
Non-Saturating Cost Method
Input Optimization Method
Adversarial Training
Logit Pairing
Fast Gradient Sign Method
6.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Which, if any, of the following propositions is true about fully-connected neural networks (FCNN)?
A FCNN with only linear activations is a linear network.
In a FCNN, there are connections between neurons of a same layer.
In a FCNN, the most common weight initialization scheme is the Zero initialization, because it leads to faster and more robust training
None of the above
7.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
How many layers Deep learning algorithms are constructed?
2
3
4
5
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