Working Paper: Machine Learning and Deep Learning Model and Algorithm Selection

Working Paper: Machine Learning and Deep Learning Model and Algorithm Selection

The present working paper provides appropriate guidance for the selection of design patterns, Machine Learning (ML) and Deep Learning (DL) models & algorithms. It gives an overview of the various approaches and suggest possible connections between them. By reading the working paper, you receive insights to different dimensions of an AI project. With this support, you will be able to evaluate your current projects and decide if you refine them to be AI-ready. Finally, the working paper presents the benefits of ML or DL deployments.
This working paper shows an intermediate state of various ongoing activities in relation to Artificial Intelligence and Project Management at the Ferdinand-Steinbeis-Institute. These activities will result in a toolset that support organizations to be more agile and data-driven – providing transparency in order to make the right decisions at the right time.

Wissenschaftlicher Mitarbeiter / Research Assistent
Senior Research Fellow