InfoWorld

How to use anomaly detection in Azure machine learning

One key part of Microsoft’s big bet on machine learning is that these technologies need to be democratized, turned into relatively simple-to-understand building blocks that Microsoft’s developer ...

Yihong Zou Advances Network Infrastructure Security Through Intent-Driven Verification Systems and Distributed Monitoring Architectures

An integrated intent-driven verification and distributed monitoring framework strengthens network infrastructure security by uniting real-time ...
Statetechmagazine

State and Local Agencies Can Identify Cyberthreats Through Anomaly Detection

Doug Bonderud is an award-winning writer capable of bridging the gap between complex and conversational across technology, innovation and the human condition. By defining a set of normal user and ...

MicroEJ and Boon Logic Partner to Simplify Edge AI with Unsupervised Learning for All Embedded Devices

Pico AI IP powered by Boon Logic and MicroEJ provides unsupervised machine learning at the Edge The endeavor brings ...
TechCrunch

Financial firms should leverage machine learning to make anomaly detection easier

Anomaly detection is one of the more difficult and underserved operational areas in the asset-servicing sector of financial institutions. Broadly speaking, a true anomaly is one that deviates from the ...
Forbes

Management AI: Anomaly Detection And Machine Learning

When a person drives, there are many things that are quickly noticed and then ignored. What gains attention are those things that might be a danger. A pedestrian who might walk out into the road, a ...
InfoQ

Anomaly Detection for Time Series Data with Deep Learning

Key Takeaways Neural nets are a type of machine learning model that mimic biological neurons—data comes in through an input layer and flows through nodes with various activation thresholds. Recurrent ...