Workshop on building a deep Bayesian networks using Monte Carlo dropout estimations.

Aim: This is a hands-on workshop to understand deep Bayesian networks. During this workshop, a deep Bayesian network using Monte Carlo dropout estimations will be constructed using Tensorflow & Keras. Once the network is built, it will be trained on a machine vision problem & generate predictions along with model specific uncertainty metrics.

Targeted audience:
General public interested in understanding deep Bayesian networks.

Minimum requirements:
Basic understanding of either R or Python 3
Interest in building deep neural networks
Basic understanding of data-science, AI & ML
Kaggle account

Important:
This is a ticketed event. Tickets available here: https://www.moad.computer/store/p36/Healthcare_Analytics.html
This is a bring your own device event. Remember to bring your laptop or a tablet to work on the projects. This is an introductory workshop on deep Bayesian networks. This course is part of the FutureReady boot-camp by Moad Computer. If you are interested in participating in the boot-camp, please fill-out this form: https://goo.gl/forms/TzClAtTqOLwHcudv1

To join remotely via Google Hangouts Meet:
meet.google.com/wme-cwwp-ira

Disclaimer: The goal of the event is not to diagnose any specific condition. That is the role of trained healthcare professionals. This event is aimed at educating how healthcare artificial intelligence works for the benefit of individuals interested in contributing to the healthcare technology ecosystem. This event also acts as a networking event for individuals interested in healthcare AI.