Tag: Unsupervised Machine Learning

Defeating Mass Registration with Unsupervised Machine Learning

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Advanced algorithms, big data analytics, and real-time detection capabilities are empowering marketplaces and social…

Advanced algorithms, big data analytics, and real-time detection capabilities are empowering marketplaces and social platforms to detect fraud holistically and act decisively.

Fraud Modeling with Automation, Complete Control, and Domain Expertise

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Discover how to build, test and deploy high-performance fraud models in a matter of minutes, instead of days.

Fraud model building must be rapid enough to respond to fraud threats and abuse in real time. DCube facilitates collaboration between fraud and data science teams to build models, review detection results, compare models, improve performance, and deploy in production for enhanced efficiency.

How UML Detects Fraud and Abuse in the Digital Era: Yinglian Xie at the Microsoft Startup Showcase

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Yinglian Xie describes how unsupervised machine learning is uniquely capable of fighting modern fraud at scale.

DataVisor Co-Founder and CEO Yinglian Xie discusses unsupervised machine learning at the 2018 Microsoft Startup Showcase.

A Few Key Differences Between Supervised and Unsupervised Machine Learning

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An overview of how to choose between supervised and unsupervised ML.

In this guide, we will explain a few high level differences when it comes to choosing between supervised and unsupervised machine learning.