AI Assistant—Annotation, validation and QC for algorithm training
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I contributed to the annotation, validation, and quality control of datasets to support the training of machine learning algorithms. My primary role was to ensure that data used for AI model development met rigorous accuracy and consistency standards. This work involved hands-on review and manual evaluation for correctness and relevance in a remote setting.
• Reviewed and annotated large volumes of textual data for natural language processing (NLP) purposes.
• Validated and rated data to improve machine learning outcomes and minimize bias.
• Ensured adherence to project guidelines and maintained data integrity throughout processes.
• Collaborated with the team on feedback loops to enhance labeling practices and achieve optimal data sets.
I contributed to the annotation, validation, and quality control of datasets to support the training of machine learning algorithms. My primary role was to ensure that data used for AI model development met rigorous accuracy and consistency standards. This work involved hands-on review and manual evaluation for correctness and relevance in a remote setting. • Reviewed and annotated large volumes of textual data for natural language processing (NLP) purposes. • Validated and rated data to improve machine learning outcomes and minimize bias. • Ensured adherence to project guidelines and maintained data integrity throughout processes. • Collaborated with the team on feedback loops to enhance labeling practices and achieve optimal data sets.
2022 - 2023