Introduction to Machine Learning Methods for Social Network Analysis

The Software and Knowledge Engineering Research Group would like to invite people who are interested in Social Network Analysis to attend a workshop hosted by SKERG that will take place from 23/04/2012 until 25/04/2012. [Download Course Materials]

Workshop Description:   

The aim of this course is to familiarize the participants with the inner work of the most common machine learning algorithms. Methods will include clustering, regression, classification and dimensionality reduction. The focus will be on “why” these algorithms work as opposed to just enumerating each algorithm’s steps. Applications of social network analysis for these methods will be demonstrated on real datasets as well as introduction to some machine learning software. 

Pre-requisites:

It is expected that the participants have some basic information technology or computer science or engineering background. The course will focus on how and why these methods work which will involve some mathematical derivation, therefore some basic knowledge of calculus and matrix algebra is required. The attendants should at least master one programming language

About The Presenter:

The course will be delivered by Mr. Ibrahim Almosallam a researcher from the Computer Research Institute at King Abdulaziz City for Science and Technology (KACST). Mr. Almosallam has a Master of Science in Computer Science from the University of Missouri-Columbia and a Bachelor of Science in Computer and Information Science from King Fahd University of Petroleum and Minerals. Mr. Almosallam’s Masters’ Thesis was in Machine learning and Data Mining and it has been his research focus since then. He has been working at KACST for two years in problems such as Automatic Speech Recognition, Text-to-Speech and Social Network Analysis. Mr. Almosallam also spent six months working with the machine-learning group at Stanford University as a visiting scholar.

Course Program:

Dates and Schedule:

The workshop will last three days starting Monday April 23th until Wednesday the 25th of April. It will consist of daily two hour sessions, from 1:00PM to 3:00PM.

Resources:

Open source tools: Weka and Orange

Machine Learning Course by Dr. Andrew Ng. from Stanford University

Relevant CfP: Social Computing at HCI International and ACM's SNA workshop

Location:

King Saud University, Malaz Campus

Building 20, Room 115 in the Admin/Male Sectio