Optimizing Hyperparameters for Machine Learning Algorithms in Production - Jonathan Krauß
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Machine learning offers the potential to train data-based models and therefore to extract knowledge from data. One key design decision is the selection of hyperparameters of a machine learning algorithm. Hyperparameter optimization techniques automatically tune the hyperparameters ¿ but choosing the best technique depends highly on the use case. This book presents a decision support system for the selection ... Pilns apraksts
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Aprašymas
Machine learning offers the potential to train data-based models and therefore to extract knowledge from data. One key design decision is the selection of hyperparameters of a machine learning algorithm. Hyperparameter optimization techniques automatically tune the hyperparameters ¿ but choosing the best technique depends highly on the use case. This book presents a decision support system for the selection of hyperparameter optimization techniques in the production domain.
Vairāk informācijas
| Autors | Jonathan Krauß |
|---|---|
| Izdevējs | Apprimus Verlag |
| Izlaides gads | 2022 |
| Vāka tips | Mīkstais vāks |
| EAN | 9783985550203 |