Introduction to Deep Learning
Wednesday, Nov. 2, 1:30-4:30 p.m.
Prerequisite: Some programming experience in Python for the hands-on portion.
It provides a high-level overview of the key elements of neural networks and deep learning (BP, CNN, LSTM), along with 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 build their own deep models using prepared software (Keras and Tensorflow) working in the browser. All necessary code is provided, however a basic level of Python programming experience is needed.
A laptop or desktop with the latest version of the Chrome browser, and a Google account for using Google Drive.
This session will be delivered online.
Participants must register using their institutional / organizational email address (not a personal email, ie. gmail).
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Presented by ACENET