Data Annotation — Learn free

Self-check

Questions 1–10 of 10

1. How is Data Annotation related to Data Labelling?
Question 1A. Data Annotation is a single step within Data LabellingB. Data Annotation is the technique of doing Data LabellingC. Data Annotation replaces Data Labelling in modern practiceD. Data Annotation is used for unsupervised learning and Data Labelling for supervised learningE. They are unrelated activities performed by different teams
2. Which of Data Annotation and Data Labelling is the broader activity?
Question 2A. Data Labelling, because it contains many annotation stepsB. Neither; they are identical in scopeC. Data Labelling, because it is done by humansD. Data Annotation, because it is only used for imagesE. Data Annotation, because it is a complete process with many steps, of which Data Labelling is one
3. What are Data Labelling tags used for by Machine Learning models?
Question 3A. Future pattern recognitionB. Encrypting the training dataC. Choosing the database engineD. Scheduling batch jobsE. Compressing the dataset
4. What is the purpose of treating Data Annotation as a process?
Question 4A. To increase the number of manual reviewersB. To slow down model training for safetyC. So that Data Labelling can be automated for accuracy, eliminating human interventionD. To keep labelled data out of ML modelsE. To convert unstructured data into relational tables
5. For which kind of Machine Learning does Data Annotation prepare data?
Question 5A. Unsupervised learningB. Reinforcement learningC. Federated learningD. Supervised learningE. Transfer learning
6. Which activity is noted as still being done manually in many organisations?
Question 6A. Model deploymentB. Data backupC. Data LabellingD. Schema designE. Log rotation
7. What can bad Data Labelling lead to?
Question 7A. An adverse impact on the outcome of applicationsB. Faster model trainingC. Reduced storage costsD. Automatic correction by the ML modelE. No effect, since annotation catches every error
8. Which of the following statements about Data Annotation is NOT correct?
Question 8A. It works together with Data Labelling to prepare datasets for ML modelsB. It is the technique for tagging data so ML models can reuse itC. It is about recognising data via a processD. It stores prepared data for future referenceE. It is a single step within the larger process of Data Labelling
9. What do Data Annotation and Data Labelling together prepare?
Question 9A. Network security policiesB. Financial statementsC. Backup schedulesD. Datasets for Machine Learning models in Data Science practiceE. Database indexes
10. Besides preparing data as input for a model, what else does Data Annotation do with the data?
Question 10A. Deletes it once the model is trainedB. Stores it for future referenceC. Encrypts it with the model's keyD. Publishes it to external partnersE. Converts it into a dashboard