MLPro — An integrative middleware framework for standardized machine learning tasks in Python
Detlef Arend, Mochammad Rizky Diprasetya, Steve Yuwono, Andreas Schwung
Abstract
In recent years, many powerful software packages have been released on various aspects of machine learning (ML). However, there is still a lack of holistic development environments for the standardized creation of ML applications. The current practice is that researchers, developers, engineers and students have to piece together functionalities from several packages in their own applications. This prompted us to develop the integrative middleware framework MLPro that embeds flexible and recombinable ML models into standardized processes for training and real operations. In addition, it integrates numerous common open source frameworks and thus standardizes their use. A meticulously designed architecture combined with a powerful foundation of overarching basic functionalities ensures maximum recombinability and extensibility. In the first version of MLPro, we provide sub-frameworks for reinforcement learning (RL) and game theory (GT).