8 Questions
What is one way to create labeled datasets?
Asking human labelers to annotate the data
Why is data labeling sometimes time-consuming?
The need for human examination and annotation
What is a potential issue with data labeling in terms of quality consistency?
Subjective nature of annotation
Why might annotators not fully understand the task in data labeling?
Not receiving proper guidelines
How can one ensure the quality of collected data in data labeling?
Labeling the same small data across multiple annotators
What is a key aspect of Data Versioning and Tracking?
Providing description and tracking changes
Why is it important to document exact changes in data versioning?
To track and understand modifications over time
What can be a challenge when tracing changes in large datasets over time?
Difficulty in tracking changes due to dataset size
Learn about the importance of combining model-centric and data-centric strategies for optimal results in data science. Explore different stages in a dataset pipeline including data ingestion, collection, processing, storage, and querying.
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