Description
Thanks to the openness of the machine learning community, any developer with an interest in machine learning these days, can get up a model to recognise characters or generate Trump-like tweets in a couple of hours. But what happens when we need to train a model to do a customer facing task, that we trust enough to deploy to a production system? And how do we get that model into production and maintain it once it is there?
My talk aims to share some of the struggles, trade-offs and strategies from the trenches of training and building the infrastructure for a complex deep learning model for production use.
The talk is aimed at tech leads and developers who are interested in machine learning and are working on training their own models that they'd like to deploy