Pre-quiz-Intro-to-ML

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This quiz is based on pre-requisites for the first topic of the machine learning module. You should be able to finish this quiz in 10-15 minutes.

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Which of these metrics is/are used to evaluate the performance of a machine learning model

2 points

Loss

Accuracy

F1 score

Mean squared error

Which one is the correct definition of the hyper-parameters of a machine learning algorithm?

1 point

They are the parameters which would be learned by the machine itself.

They are the parameters which we supply to the model to optimize its performance.

Clear selection

Over-fitting causes:

1 point

good generalization behaviour on new data.

poor generalization behaviour on new data.

Clear selection

In which phase does the parameter tuning occur for optimizing the selected model?

1 point

training phase

validation phase

testing phase

Clear selection

The process of adding information in order to solve an ill-posed problem or to prevent overfitting is called:

1 point

Generalization

Regularization

Optimization

Clear selection

Why normalization is necessary for machine learning?

1 point

What is machine learning?

1 point

The autonomous acquisition of knowledge through the use of computer programs.

The autonomous acquisition of knowledge through the use of manual programs.

The selective acquisition of knowledge through the use of computer programs.

The selective acquisition of knowledge through the use of manual programs.

Clear selection

Which of the following sentence(s) is/are FALSE regarding regression?

2 points

It relates inputs to outputs.

It is used for prediction.

It may be used for interpretation.

It discovers causal relationships.

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