james537/ml-networking

Machine Learning Applied to Networking

Machine Learning for Networking

This repository contains exercises, resources, and information for learning machine learning concepts and applying them to networking.

Videos and Readings

• Networking videos will provide networking background.
• Videos on machine learning topics will also be posted.

Structure

A general structure for a short course on this material is as follows. Each lecture has (1) a set of slides explaining concepts, (2) an accompanying Jupyter Notebook with example applications from networking to make the concepts more concrete and further expand on networking concepts, (3) some basic background reading on the topic.

Lecture	Topic	Lab	Preparation
1	Machine Learning/Python Basics	Python Basics
2	Network Measurement	Traffic Analysis	Videos: 1-9, 26, 85-94
3	Linear Regression	IoT: Energy Prediction
4	Logistic Regression	DNS Query Detection
5	Naive Bayes	Spam Filtering
6	Nearest Neighbor/Trees/Ensemble	Activity Recognition
7	Unsupervised Learning	Traffic Clustering
8	Deep Learning	DDoS Detection

Please come to class having done the reading.

Each week will also have a short homework assignment and a short accompanying quiz to track your knowledge of the material.

Repository

The repository has the following organization:

• pcaps/ - example packet captures used in notebooks
• data/ - other data used in notebooks (non-pcap)
• lectures/ - slides for each lecture
• notebooks/ - notebooks for each lecture
• reading/ - reading for lectures, as applicable