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Developing Open Source Educational Resources for Machine Learning and Data Science.

, , , , , , and . Teaching ML, volume 207 of Proceedings of Machine Learning Research, page 1-6. PMLR, (2022)

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Improving Accuracy of Interpretability Measures in Hyperparameter Optimization via Bayesian Algorithm Execution, , , and . (2022)Tunability: Importance of Hyperparameters of Machine Learning Algorithms., , and . Journal of Machine Learning Research, (2019)Uncertainty Quantification for Deep Learning Models Predicting the Regulatory Activity of DNA Sequences., , , , and . ICMLA, page 566-573. IEEE, (2023)Quantifying Interpretability of Arbitrary Machine Learning Models Through Functional Decomposition., , and . CoRR, (2019)Robust and Efficient Imbalanced Positive-Unlabeled Learning with Self-supervision., , , and . CoRR, (2022)Semi-Structured Deep Piecewise Exponential Models., , , , , and . CoRR, (2020)mlr3pipelines - Flexible Machine Learning Pipelines in R., , , , , and . J. Mach. Learn. Res., (2021)fmeffects: An R Package for Forward Marginal Effects., , , , and . CoRR, (2023)Mind the Gap: Measuring Generalization Performance Across Multiple Objectives., , , , , and . IDA, volume 13876 of Lecture Notes in Computer Science, page 130-142. Springer, (2023)Neural Architecture Search for Genomic Sequence Data., , , , , , , and . CIBCB, page 1-10. IEEE, (2023)