Chris Powell, chief technology officer at NT Concepts, has said that integrating machine learning into DevOps practices can help organizations leverage the emerging technology’s maximum value for enterprise-wide operations.
Powell wrote in a blog post published Tuesday that Machine Learning Operations enable ML models to “learn” throughout iterative development procedures using structured and unstructured data types.
He noted that MLOps models are meant to support tasks like signal classification, natural language processing and object detection while automating data analysis approaches to free up employee’s time for higher-level functions.
An MLOps pipeline is also meant to allow multiple team members to access ML models and support integration with traditional technologies for data processing and management, Powell added.
“Machine learning is a broad field that includes a wide range of expectations,” he said. “Using a MLOps approach can help your agency continuously iterate, refine, and deploy models at an enterprise level. Holistically, this leads to significantly better outcomes and results for your Intelligence analysts and decision makers.”