Multilingual Text Intent and Sentiment Classification
Performed high-volume text classification on user-generated content to improve sentiment analysis and intent detection models. Tasks included identifying customer purchase intent, flagging inappropriate content, and categorizing support tickets into hierarchical taxonomies. Consistently maintained a 98% accuracy rating across 5,000+ individual tasks.