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 specific interest in […]

We hear a lot about Big Data, Data Science, Data Analytics and Artificial Intelligence in the news. Join the Acadia Institute for Data Analytics, who will clarify these terms and provide a sense of the Data Analytics process for business owners, managers and other professionals who may be considering related projects. The talk will provide an overview of Data Science, Data Analytics and Big Data. We will explore the relationship between Data Analytics and Business Intelligence with an emphasis on required resources and best practices for success. Along the way you will learn the basics about Data Warehousing, Data Engineering, and Data Visualization and gain a sense of how Data Mining methods and Machine Learning technology work to develop predictive models. We conclude with end with an examination of current trends in Data Analytics and key considerations and best practices for getting started in Data Analytics.