Data Labelling — Learn free

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Questions 1–10 of 10

1. What is Data Labelling?
Question 1A. Encrypting data so that its source cannot be identifiedB. Grouping data based on an existing parameter without any taggingC. Tagging something that is not identifiable when it comes from the source, based on a defined parameterD. Deleting data that cannot be identifiedE. Converting data from one format to another
2. On which kinds of data can Data Labelling be performed?
Question 2A. Both known data and unknown dataB. Known data onlyC. Unknown data onlyD. Structured data onlyE. Numeric data only
3. On what basis does Data Classification group data?
Question 3A. Random samplingB. Existing parameters only, with no human inputC. The size of each recordD. The order of arrivalE. Manually labelled data
4. On what basis does Data Clustering group data?
Question 4A. Manually labelled dataB. An existing parameterC. Business requirementsD. A training datasetE. Customer feedback
5. Why do specialised tools exist to tag or label unstructured datasets?
Question 5A. To compress the data for cheaper storageB. To delete duplicate filesC. To convert the data into relational tablesD. So the unstructured data can become input for Machine Learning modelsE. To satisfy backup regulations
6. What can unstructured data labelled by an ML library then be used for?
Question 6A. Only for archival purposesB. As input to another ML model for Supervised LearningC. Replacing the original source systemD. Generating database schemas automaticallyE. Encrypting the original dataset
7. Of Data Labelling, Data Classification and Data Clustering, which one falls under Unsupervised Learning?
Question 7A. Data LabellingB. Data ClassificationC. All threeD. Data ClusteringE. None of them
8. What development has driven the need for tools that label data?
Question 8A. The era of unstructured datasets, with data arriving in many formatsB. The decline of relational databasesC. A shortage of database administratorsD. The introduction of cloud billingE. The end of batch processing
9. Which statement correctly describes the relationship between Data Labelling and Data Classification?
Question 9A. Data Classification produces the labels that Data Labelling then appliesB. They are the same activity under different namesC. Data Labelling can only happen after clustering has finishedD. Data Classification never uses labelled dataE. Data Classification groups data using data that has been manually labelled
10. Which of the following is NOT true of Data Labelling?
Question 10A. It tags data based on some defined parameterB. It can be performed on unknown dataC. It can only be applied to data that is already identifiable at sourceD. Specialised tools and ML libraries can perform it on unstructured dataE. Its output can feed a Supervised Learning model