Awesome Software Engineering for Machine Learning
Software Engineering for Machine Learning are techniques and guidelines for building ML applications that do not concern the core ML problem – e.g. the development of new algorithms – but rather the surrounding activities like data ingestion, coding, testing, versioning, deployment, quality control, and team collaboration.
Good software engineering practices enhance development, deployment and maintenance of production level applications using machine learning components.
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