An Introduction to Deep Learning with Neural Networks
March 20, 2019 - March 20, 2019 (6:00 pm - 9:00 pm)
Workshop Leads: Dr. Danny Silver & Dr. Andy McIntyre
Host: Acadia Institute for Data Analytics
Date/Time: Wednesday, March 20, 2019 from 6pm - 9pm
Location: Patterson Hall, Classroom 213
Abstract: This tutorial will provide a gentle hands-on introduction to developing predictive models using deep learning artificial neural networks. We will provide 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 such as object recognition in images (e.g. classification of animal or letter) and sequence prediction (e.g. next word in a sentence, like Google auto-complete). Participants will get to build their own deep models using prepared software (Keras and Tensorflow) working in the browser.
Prerequisites: All Python code will be provided, but some programming experience would be beneficial. Participants will need to bring a laptop with the latest version of the Chrome browser running on it, and a Google account for using Google Drive.
Objectives: To provide a hands-on workshop that is fun and informative for participants. Covers 500-foot fundamentals of neural networks and deep learning (BP, CNN, LSTM) using popular python programming libraries.
Who is this for: Students, faculty, researchers, company employees, and business executives who are seeking an introduction to deep learning technology.
Registration: Please register here to ensure adequate space for everyone. Participants must register by March 18th and complete a short study prior to the workshop. Details on this preparatory study will be sent to registrants.
An evening snack and refreshments will be provided.