Machine Learning for Networks

This 45-hour course focuses on understanding the basics of Machine Learning and applying it to problems in Computer Networks. I was responsible for part of it.

Lectures:

  • Introduction:
  • Regression
  • Regression (continued) and Classification
  • Neural Networks
  • Trees and Ensembles
  • Unsupervised Learning: Clustering and Anomaly Detection
  • Dimensionality Reduction for Anomaly Detection and Supervised Learning

External Expert Lectures:

  • Dimensionality Reduction and Network Anomalies
  • Machine Data Analysis with Elastic Stack
  • Predictive Maintenance
  • Machine Learning for High-Speed Networks
  • Collecting and Processing Network Data
  • Intrusion Detection from Network Traces