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