Learn to detect anomalies in large data sets to identify network intrusions using supervised and unsupervised machine learning techniques, such as accelerated XGBoost, autoencoders, and generative adversarial networks (GANs).
PREREQUISITES: Experience with CNNs and Python
TOOLS AND FRAMEWORKS: Keras, GANs
LANGUAGES: English
DURATION: 2 hours