Authors:
Martin Lindvall, Jesper Molin, Jonas Löwgren
From a human-centered perspective, one of the most important developments in the technical machine-learning (ML) domain is that learning algorithms can now improve their predictions when fed more training data. This means that processes and tools for generating training data, previously a matter mostly for one-off research projects, now have a large impact on the success of ML projects. In many domains, the designers and engineers of machine-learning-based systems do not themselves hold the expertise required to create training data. In a typical project, the creation and curation of data might require many man-months of effort and involve the…
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