Check out our paper to see how the power of visualization fulfilled the operational needs of our industry research team to detect and resolve the frequently seen issues in our productionized operational security models. We described the full step-by-step design of the user interface and shared the lessons we learned, and demonstrated how we used the system. We added multiple simple views rather than one complex view to support data scientists’ workflow while keeping it simple for high-level users. We focused on finding trends and anomalies in data feeds relevant to the models. A combination of several charts enabled the team to ask questions, verify their hypotheses and generate insights.
SophosAI team develops numerous machine learning models that get directly integrated to our products. Currently we have more than 30 models deployed […]
One of the best-known secrets of machine learning (ML) is that the most reliable way to get more accurate models is by getting more training data and more accurate labels. Learn about the ways that our engineering team build systems to handle the volume of data required for our state-of-the-art security model.
Generating up to date, well labeled datasets for machine learning (ML) security models is a unique engineering challenge, as large data volumes, complexity of labeling, and constant concept drift makes it difficult to generate effective training datasets. Here we describe a simple, resilient cloud infrastructure for generating ML training and testing datasets, that has enhanced the speed at which our team is able to research and keep in production a multitude of security ML models.