It is the goal of this research to identify what the main challenges are, by applying an interpretive research approach in close collaboration with companies of varying size and type. There is a clear lack of well-functioning tools and best practices for building DL systems. For companies without large research groups or advanced infrastructure, building high-quality production-ready systems with DL components has proven challenging.
Many of these achievements have been reached in academic settings, or by large technology companies with highly skilled research groups and advanced supporting infrastructure. Surprisingly promising results have been achieved by deep learning (DL) systems in recent years.
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