Home > Servers > Modular Servers > White Papers > Reference Architecture: Machine Learning Containers on PowerEdge MX and VMware Cloud Foundation 4.0 with Tanzu > Introduction
To demonstrate how this platform will be used in a typical production environment, we leverage two real-world business problems that are solved using a common retail machine learning framework.
These two common cases can be found as part of the Grid Dynamics Services Portfolio:
These two solutions are being provided by open-source code via the Dell Github and are a great starting point for a journey into using the proposed machine learning reference platform.
While the platform could accommodate any type of workload, it is advised to use optimized models/libraries to get best results, like ones that are based on XGBoost (and its accelerated version Intel DAAL XGBoost). To get best results and reduce the training time for image processing, the server platform needs to be extended with GPUs.
Link to source code for use cases: https://github.com/dell/iDRAC-Telemetry-Scripting/blob/master/pipelines%20(1).zip