This study aims to explore the data management challenges encountered by practitioners developing systems with DL components, identify the potential solutions�...
Data management is one of the most prominent challenges which complicates DL in industrial deployments. DL models are data-hungry and require high-quality data.
Jun 22, 2022 � This study aims to explore the data management challenges encountered by practitioners developing systems with DL components, identify the potential solutions�...
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Data management for production quality deep learning models: Challenges and solutions � AI Deployment Architecture: Multi-Case Study for Key Factor�...
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Aug 16, 2024 � This article will review ML and AI's role in data quality management, from the benefits and challenges of AI/ML-driven data quality to our best practices.
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We will cover data collection and quality challenges in the first three steps from data collection to model training. data becomes a first class citizen, on par�...
Jun 28, 2023 � Key Challenges in Data Management for Machine Learning � Many datasets � Datasets are dynamic � Linking datasets to trained models � Metadata and�...
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Mar 26, 2024 � The research presents the Data Quality Funnel Model to improve business decision-making and flexibility, by making data more accurate, reliable, and valuable�...
Apr 29, 2024 � Accurate labeling and annotation are crucial for reliable ML systems, but applying complex ontologies consumes up to 80% of AI project time.
Apr 3, 2023 � This report provides an overview of the challenges that arise in data management and the solutions that can help overcome these challenges.