Frater is a machine learning and data-driven systems framework designed to modularize pipelines into various components. This allows for more flexibility in building and deploying machine learning systems. Developed by John Henning during his tenure at IBM Research, Frater is aimed at enabling researchers and engineers to construct effective and functional machine learning workflows. The tool has a focus on deep learning applications, specifically in the areas of computer vision and activity detection.
• supports machine learning workflows
• flexibility in system design
• modular pipeline construction
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