Course Overview
Learn to detect anomalies in large datasets to identify network intrusions using supervised and unsupervised machine learning techniques, such as accelerated XGBoost, autoencoders, and generative adversarial networks (GANs).
Prerequisites
- Professional data science experience using Python
- Experience training deep neural networks
Course Objectives
- 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