The focus for this MeetUp's main talks will be on understanding what Deep Learning models are actually doing. Even if you're getting great results, being able to explain *why* may well be of interest. And if you haven't started Deep Learning yet - and may be being held back by doubts about 'black box behaviour' - then this MeetUp will also be relevant.
FWIW, Pedro Domingos recently sent out the following 'scare tweet' about the GDPR :
"""Starting May 25, the European Union will require algorithms to explain their output, making deep learning illegal."""
(unless you attend this talk, of course).
Planned Talks :
"Explainable Models : A Primer" - Hardeep Arora
Hardeep's talk approaches the explainability topic from more of a data science angle : So that we can see what the issues are, and contrast the techniques with those that are being discovered for Deep Learning.
"Explainable AI : Shapley Values and Concept Activation Vectors" - Lee XA
Xiong An is a Senior Research Officer from the Imaging Informatics Division of A*STAR, Bioinformatics Institute. He is passionate about the applications of deep learning onto unexplored areas and is currently using deep learning and machine learning to improve crop yields in smart urban farms. His training is in computational biology and holds a bachelor's degree in Science from NUS.
"Did the Model Understand the Question?" - Martin Andrews
This talk should be pretty 'accessible', even though it describes the work from a recent paper. Specifically, Martin will describe how Question Answering for Images works, and then show how to 'deconstruct' what the network is doing. Sometimes with surprising results.
We also have a confirmed lightning talk on KubeFlow (and how it can be used to automate Jupyter deployments) - any other lightning talks will be warmly accepted : Please check in with Martin at the start of the event.
If you have something that you'd like to present in a welcoming environment, please let us know by suggesting yourself via the /suggestion/ link given below... We're very enthusiastic about Lightning Talks, which are a great way of showing people cool stuff that you've been working on, without the (imagined) pressure of the "Full Presentation".
Talks will start at 7pm (A/V equipment permitting) and end at around 8:45pm, at which point people normally come up to the front for a bit of a chat with each other, and the speakers.
As always, we're actively looking for more speakers for future events - both '30 minutes long-form', and lightning talks. For the lightning talks, we welcome folks to come and talk about something cool they've done with TensorFlow and/or Deep Learning for 5-10mins (so, if you have slides, then #max=10). We believe that the key ingredient for the success of a Lightning Talk is simply the cool/interesting factor. It doesn't matter whether you're an expert or and enthusiastic beginner: Given the responses we have had, we're sure there are lots of people who would be interested to hear what you've been playing with.
Please suggest yourself here :