This tutorial will provide a gentle hands-on introduction to developing predictive models using deep learning artificial neural networks. It 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.
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.
The workshop is aimed at students, faculty, researchers, company employees, and business executives who are seeking an introduction to deep learning technology.
Registration deadline 18 March.