Recent advancements in linked devices and industrial automation have created a large demand for network resources. The amount of traffic created by these technologies is so great that traditional networks are becoming less capable of handling it. Network automation is made possible by Machine Learning (ML) applications using Software Defined Networking (SDN), which simultaneously presents a programmable, reconfigurable, and scalable networking solution. This SDN system can address problems with conventional approaches to categorize network traffic and assign resources. The SDN controller will collect network data that data analytic techniques may analyze and use ML models to tailor network management. The paper proposes to analyze network data, apply ML to classify network traffic, and integrate the model into LabVIEW.