Applications of AI for Anomaly Detection

In this workshop, you’ll learn how to implement multiple AI-based approaches to solve a specific use case of identifying network intrusions for telecommunications. You’ll learn three different anomaly detection techniques using GPU-accelerated XGBoost, deep learning-based autoencoders, and generative adversarial networks (GANs) and then implement and compare supervised and unsupervised learning techniques. At the end of the workshop, you’ll be able to use AI to detect anomalies in your work across telecommunications, cybersecurity, finance, manufacturing, and other key industries

• Prepare data and build, train, and evaluate models using XGBoost, autoencoders, and GANs
• Detect anomalies in datasets with both labeled and unlabeled data
• Classify anomalies into multiple categories regardless of whether the original data was labeled

Experienced Data Scientists

• Professional data science experience using Python
• Experience training deep neural networks