Data Programming

Data programming leverages programmatic labeling functions to efficiently generate training data for machine learning models, addressing the challenges of limited labeled datasets. Current research focuses on improving the accuracy and coverage of these automatically generated labels, often employing techniques like active learning to strategically select data points for human annotation and incorporating knowledge bases to enhance label quality. This approach holds significant promise for accelerating model development across diverse fields, from healthcare data analysis to computer vision and natural language processing, by reducing the reliance on extensive manual labeling efforts.