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Upcoming Workshop: Applications of AI for Anomaly Detection

Learn to detect data abnormalities before they impact your business by using XGBoost, autoencoders, and GANs. Workshops are available in both the NALA and EMEA... < 1
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Explain Your Machine Learning Model Predictions with GPU-Accelerated SHAP

Machine learning (ML) is increasingly used across industries. Fraud detection, demand sensing, and credit underwriting are a few examples of specific use... 15 MIN READ
Technical Walkthrough 1

Real-time Serving for XGBoost, Scikit-Learn RandomForest, LightGBM, and More

The success of deep neural networks in multiple areas has prompted a great deal of thought and effort on how to deploy these models for use in real-world... 7 MIN READ
Technical Walkthrough 0

Accelerating Trustworthy AI for Credit Risk Management

On April 21, 2021, the EU Commission of the European Union issued a proposal for a regulation to harmonize the rules governing the design and marketing of AI... 12 MIN READ
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NVIDIA DLI Teaches Supervised and Unsupervised Anomaly Detection

The NVIDIA Deep Learning Institute (DLI) is offering instructor-led, hands-on training on how to build applications of AI for anomaly detection.  Anomaly... 5 MIN READ
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Learn How to Build Applications of AI for Anomaly Detection

Whether you need to monitor cybersecurity threats, fraudulent financial transactions, product defects, or equipment health, artificial intelligence can help you... 2 MIN READ