DEL Test

Which of the following is not required for learning?

• A defined Task

• A Defined Evaluation method

• An adaptable automaton

• A Testing Data Set

Answer explanation

You do not need to test to learn, you will just not be able to evaluate if you did learn anything or not

Why can linear regression be seen as machine learning?

• It can linearly separate space

• More inputs and targets (experience) improve its performance

• It is used as the basis of Perceptrons

Which of these models overfits?

• The middle one

• The right one

• The left one

• None of them

• All of them

In deep learning, an activation function of a hidden layer should not :

• Have discontinuities

• Be linear

• Have a continuous derivative (except isolated points)

In order to monitor the capacity of a model we don't need:

• A training dataset

• A predetermined threshold (target value of J(w))

• A validation dataset

If my model has to predict which type of image this is, the final activation should not be:

• soft-max

• tanh

• sigmoid

• linear

• B== 1

• B <= Number of Elements in Training Dataset

• B < Number of Elements in Training Dataset

• B == Number of Elements in Training Dataset

Which of the following is true about ReLU?

• All neurons always activate positively in a ReLU layer

• It only focuses on presence, not intensity

• It is non-linear

• It fully resolved the vanishing gradient problem

Vanishing gradient happens when:

• The learning rate is too strong

• The activations of some ReLU are set to 0

• The activation functions are linear

• Consecutive derivatives multiplications tend to 0

Dropout is equivalent to which type of normalization?

• Elastic Net

• L2

• L1

• L1.5