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Pre-quiz-Intro-to-ML
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
Your answer
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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