Data Categorization & Quality Control – Academic/Self-directed
Organized and labeled 300+ text samples into predefined categories such as sentiment, topic, and intent. Performed error checking by reviewing datasets for duplicates, inconsistencies, and missing values. Documented labeling guidelines and edge cases and used these to cross-check results against reference standards. • Labeled 300+ examples with 95%+ category consistency • Reviewed datasets for duplicates, inconsistencies, and missing values • Created repeatable workflows using written guideline documentation • Conducted QA cross-checking against reference standards