The School of Computer Science at the University of Windsor is pleased to present...
Technical Workshop Presentation by
Data Clustering Workshop
Date: Tuesday, November 15th, 2022
Time: 6:00pm – 7:00pm
Location: 4th Floor (Workshop space) at 300 Ouellette Avenue (School of Computer Science Advanced Computing Hub)
LATECOMERS WILL NOT BE ADMITTED once the presentation has begun.
Abstract:
Clustering is a way of grouping data points into different clusters consisting of similar data points. The objects with possible similarities remain in a group that has less or no similarities with another group. In this workshop, we explore various clustering approaches in centralized and decentralized environments and provide various metrics for finding the accuracy and performance of clustering. We also provide basic concepts on some well-known clustering approaches and their differences, followed by the performance discussion of each of the clustering methods. In an advanced clustering session, we explore various dimensionality reduction techniques and provide basic concepts and applications for that. All the clustering techniques will come with implementations in python using scikit-learn library. This workshop will be in three parts: I- clustering in centralized environments, II- advanced topics in clustering, and III- parallel clustering in decentralized environments.
After this workshop, students will be able to: I- identify the difference between different machine learning tasks, II- work with some well-known clustering approaches and understand the concepts behind them, and III- identify the difference between centralized and parallel clustering.
Prerequisites:
Matrix algebra, statistics, basic python programming, basic C++ programming
Workshop Outline:
Advanced topics in clustering
DBSCAN and concepts
Dimensionality reduction (PCA) and its concepts
tSNE and IsoMap
The relationship between clustering and dimensionality reduction
Implementation of what has been discussed in python
Biography:
Ali is pursuing his Ph.D. in computer science at the University of Windsor. His main research interest is security/privacy in machine learning. He has some publications on private clustering and has participated in the iDash competition in 2022. He has got various scholarships from the University of Windsor, including RAs and GAs.