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Many AutoML software systems cover different requirements and perform use-case dependently. Therefore, this selection tool can help to select the most appropriate AutoML software solution for a given use-case. Requirements of the use-case are taken from a questionnaire and based on the answers, a use-value analysis and a ranking is carried out.
| Topic Fields | |
| Published | 2021 |
| Involved Institutes | |
| Project Type | Fraunhofer Project |
| Result Type | |
| Responsibles |
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This digital service "Automated Machine Learning in Production" provides an overview of the performance of multiple tools in the field of automated machine learning (AutoML).
AutoML aims at automating the manual decisions a data scientist needs to make during the creation of the ML pipeline, e.g., the choice of a suitable ML algorithm.
The digital service contains the following features:
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