Corpus ID: 129946121

The Scientific Method in the Science of Machine Learning

@article{Forde2019TheSM,
  title={The Scientific Method in the Science of Machine Learning},
  author={Jessica Zosa Forde and Michela Paganini},
  journal={ArXiv},
  year={2019},
  volume={abs/1904.10922}
}
  • Jessica Zosa Forde, Michela Paganini
  • Published 2019
  • Computer Science, Mathematics
  • ArXiv
  • In the quest to align deep learning with the sciences to address calls for rigor, safety, and interpretability in machine learning systems, this contribution identifies key missing pieces: the stages of hypothesis formulation and testing, as well as statistical and systematic uncertainty estimation -- core tenets of the scientific method. This position paper discusses the ways in which contemporary science is conducted in other domains and identifies potentially useful practices. We present a… CONTINUE READING

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