Related references
Note: Only part of the references are listed.Snorkel: rapid training data creation with weak supervision
Alexander Ratner et al.
VLDB JOURNAL (2020)
The Challenge of Crafting Intelligible Intelligence
Daniel S. Weld et al.
COMMUNICATIONS OF THE ACM (2019)
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
Cynthia Rudin
NATURE MACHINE INTELLIGENCE (2019)
European Union Regulations on Algorithmic Decision Making and a Right to Explanation
Bryce Goodman et al.
AI MAGAZINE (2017)
MediBoost: a Patient Stratification Tool for Interpretable Decision Making in the Era of Precision Medicine
Gilmer Valdes et al.
SCIENTIFIC REPORTS (2016)
Beyond Manual Tuning of Hyperparameters
Frank Hutter et al.
KUNSTLICHE INTELLIGENZ (2015)
Power to the People: The Role of Humans in Interactive Machine Learning
Saleema Amershi et al.
AI MAGAZINE (2014)
Eliciting good teaching from humans for machine learners
Maya Cakmak et al.
ARTIFICIAL INTELLIGENCE (2014)
Scratch: Programming for All
Mitchel Resnick et al.
COMMUNICATIONS OF THE ACM (2009)
IPython:: A system for interactive scientific computing
Fernando Perez et al.
COMPUTING IN SCIENCE & ENGINEERING (2007)
Interactive machine learning: letting users build classifiers
M Ware et al.
INTERNATIONAL JOURNAL OF HUMAN-COMPUTER STUDIES (2001)