Introduction to Deep Learning with Neural Networks

Introduction to Deep Learning with Neural Networks

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A gentle hands-on introduction to developing predictive models using deep learning artificial neural networks. All Python code is provided!

About this event

Workshop Leads: Dr. Danny Silver & Dr. Andy McIntyre

Format: Virtual Event via Microsoft Teams

Host: St. Francis Xavier University

Date/Time: Thursday, October 22nd from 6:00pm to 9:00pm

Price: FREE

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.

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, business professionals or anyone who are seeking an introduction to deep learning technology.

Prerequisites: All Python code will be provided, but some programming experience would be beneficial. Participants will need a laptop or desktop with the latest version of the Chrome browser running on it, and a Google account for using Google Drive.

Registration: Participants must register by October 16th and complete a short tutorial to get set-up and become familiar with Google Colaboratory prior to the workshop. Details on this preparatory study will be sent to registrants.

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