An Introduction to Deep Learning with Neural Networks
November 30, 2021 - November 30, 2021 (9:00 am - 12:00 pm)
In this hands-on webinar, Dr. Danny Silver and Dr. Andy McIntyre of the Acadia Institute for Data Analytics will share a high-level overview of the key elements of neural networks and deep learning, and recent advances that allow deep networks to solve challenging problems. Participants will engage in hands-on learning and building their own deep models using prepared software (Keras and Tensorflow).
Programming or coding experience is not a requirement for participants, as all code needed will be provided, however some programming experience will help! For this workshop, you will need a laptop or desktop with the latest version of the Chrome browser, and a Google account for using Google Drive.
Anyone who is interested in this session must register by November 23rd and complete a short study prior to the workshop (which will be sent to you).
About the Presenters
Dr. Andy McIntyre, Associate Director & Data Scientist
Andy completed a Bachelor of Science degree at Mount Allison University in 2000. Andy continued his academic pursuits at Dalhousie University, enrolling in the Masters of Computer Science Program and later graduating with a Ph.D. in the field in 2007. Andy’s focus has mainly been machine learning with a specific interest in evolutionary computation, a population-based meta learning technique for model building.
His work has most recently included a 10-year role as senior researcher with the Network Information Management and Security group at Dalhousie, working on computer gaming and behaviour mining applications. He was previously a postdoc with the department of Ophthalmology and Visual Science, investigating shape-based, predictive GP / imaging models and had further postdoctoral collaborations with National Research Council Canada Institute for Biodiagnostics Atlantic at the Neuroimaging Research Laboratory, developing models of functional connectivity with clustering and classification algorithms applied to large-scale, resting-state functional MRI (brain-imaging) data.
Andy currently holds an adjunct professor designation at Dalhousie and an adjunct position with the Jodrey School of Computer Science at Acadia University with 19 publications and has been named on five US patents as of 2020. Andy assumed the role of Data Scientist at the Acadia Institute for Data Analytics as of October 2018 and has recently taken on the role of Associate Director.
Dr. Danny Silver, Data Scientist, Acadia Institute for Data Analytics & Professor, Jodrey School of Computer Science at Acadia University
Danny is a Professor in and former Director of the Jodrey School of Computer Science at Acadia University. His areas of research and development are machine learning, data mining, user modeling, and adaptive systems. He has published over 60 scientific papers, edited special journal editions, and has been part of the organizing or program committee for a number of national and international conferences, seminars and workshops. Most recently he was awarded a Harrison McCain Foundation Award for research into advanced 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. In 2011, he received the Science Champion Award from the Nova Scotia Discovery Centre for his work on youth robotics and the advancement of STEM education.