Self-driven Data Labeling and Evaluation Practice
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Explored AI workflows including data labeling and evaluation as part of self-driven learning in computer science studies. Applied basic data annotation and evaluation techniques to sample datasets for practice and skill development. Developed familiarity with the data labeling process in support of AI model improvement and training. • Practiced labeling and annotating data using example text datasets
• Evaluated AI-related outputs for correctness through manual review
• Utilized basic annotation skills in Google Colab environment
• Improved labeling accuracy and consistency through iterative practice
Explored AI workflows including data labeling and evaluation as part of self-driven learning in computer science studies. Applied basic data annotation and evaluation techniques to sample datasets for practice and skill development. Developed familiarity with the data labeling process in support of AI model improvement and training. • Practiced labeling and annotating data using example text datasets • Evaluated AI-related outputs for correctness through manual review • Utilized basic annotation skills in Google Colab environment • Improved labeling accuracy and consistency through iterative practice
2023 - Present