Bartz & Bartz GmbH initiated the methods described in this book to achieve better results in hyperparameter tuning faster, with less effort and costs. Because, let’s face it, computational time entails a number of costs. First and foremost it entails the time of the researcher, furthermore a lot of energy. All this equals money. So if we manage to achieve better results in hyperparameter tuning in less time, everybody profits. On a larger scale the methods described may contribute a small part to address some of the challenges we face as a society.
CITATION STYLE
Bartz, E. (2023). Introduction. In Hyperparameter Tuning for Machine and Deep Learning with R: a Practical Guide (pp. 1–4). Springer Nature. https://doi.org/10.1007/978-981-19-5170-1_1
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