Introduction to Data Mining: Basics of Unsupervised and Supervised Learning

Thursday, March 5 – 5:30PM-9:00PM

Patterson Hall 224

Instructor: Danny Silver

Bio: Danny is the Director of the Acadia Institute for Data Analytics. He is also a professor in and the former Director of the Jodrey School of Computer Science at Acadia University. His areas of research and development are machine learning, data mining, and adaptive systems. He has published over 60 scientific papers and served in administrative roles for a number of national and international conferences, seminars and workshops. He is on the editorial board for the Journals of Artifical General Intelligence and Brain Informatics and was the President of the Canadian Artificial Intelligence Association (CAIAC) from 2007-2009. Danny most recently was awarded a Harrison McCain Foundation Award for research into advance machine learning methods. Since 1993, he has worked on machine learning and data mining projects in the private and public sector providing situation analysis and problem definition, project management and guidance, and predictive analytic services.

Purpose: To provide an overview of Data Analytics and introduce the basics of Data Mining through a hands-on tutorial. The WEKA Data Mining suite will be used as the tutorial tool (it installs easily on all platforms) and all participants will be provided with a set of data files to explore. We will begin with unsupervised machine learning using the k-means clustering algorithm and then move on to supervised learning to make predictions using the k-NN and Decision Tree algorithms.

Audience: Wide cross-section: students, faculty, staff, business and industry persons. All participants must bring their own laptop, and should be comfortable with using tools such as Excel, web browsers, etc.

Resources/Materials:

- Classroom setting for up to 30 people

- Each participant (or pair of participants) must bring their laptop and be able to connect to the Internet.

- All cross-platform software will be downloaded from the web or run on a browser

- There will be coffee, tea, juice, cookies and fruit available at 5:30pm that will last through to the 7:15pm break.

Schedule:

5:30 – Registration and refreshments

6:00 – Welcome and introduction to data analytics

6:20 – Installation of WEKA software and first tutorial – load in some data and check it out

6:40 – Unsupervised learning, k–means basics

7:00 – K–means tutorial

7:20 – Break

7:40 – Supervised learning, k-NN basics

8:00 – K–NN tutorial

8:20 – Decision tree basics

8:40 – Decision tree tutorial

9:00 – Close

This workshop costs $15 to cover food and interested people must register by Tuesday March 3rd, 2015 @ 4:30PM.