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Online workshop: Targeted selection of suitable AI parameters
The digital transformation is in full swing. But even though AI is now part of common parlance, the targeted selection of suitable data is often the central hurdle to implementation. In this workshop of the Mittelstand-Digital Zentrum Augsburg, you will receive an overview of the potential of systematic data and feature selection.
- German
The digital transformation is in full swing. But even though AI is now part of common parlance, the targeted selection of suitable data is often the central hurdle to implementation. In this workshop of the Mittelstand-Digital Zentrum Augsburg, you will receive an overview of the potential of systematic data and feature selection.
Topics covered include data types, data quality and data analysis, standardized data interfaces, and feature engineering. Using the PPR model (product, process, and resource), you will work together to identify suitable data from a sample plant and examine a sample data set in an exploratory data analysis. Using practical examples from the areas of quality assurance, maintenance, and process optimization, we will show you how to build robust data sets.
Contents
The importance of data for AI applications
The relationship between data and model quality
Standardized data interfaces
Implementation examples at Fraunhofer IGCV
Target audience
The online workshop is aimed at plant managers and planners, manufacturing executives, and process experts. No prior knowledge is required.
Register now for free! The access data will be sent to you by email in good time.
