Applications of AI for Anomaly Detection

About this course

Detect what does not belong in your data. In this hands-on day you will prepare network data and train GPU-accelerated XGBoost, autoencoder and GAN models to find and classify anomalies in both labelled and unlabelled datasets.

What you'll learn

• 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

Curriculum

Who it's for

Data scientists, security analysts and engineers working with telemetry, network or transaction data.

Before you start

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