• Corpus ID: 226143754

Interactive machine learning for user-innovation toolkits : an action design research approach

@inproceedings{Bernardo2020InteractiveML,
  title={Interactive machine learning for user-innovation toolkits : an action design research approach},
  author={Francisco Bernardo},
  year={2020}
}
Machine learning offers great potential to developers and end users in the creative industries. However, to better support creative software developers' needs and empower them as machine learning users and innovators, the usability of and developer experience with machine learning tools must be considered and better understood. This thesis asks the following research questions: How can we apply a user-centred approach to the design of developer tools for rapid prototyping with Interactive… 

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