Our Rabbiteer sessions are our way of bridging the gap between university and the working world as well as a way to upgrade your workplace. With the fast advancement of tech, we make sure you never miss out by giving experts a platform to keep you in the loop.
Jade Abbott is a Machine Learning engineer at Retro Rabbit. She's built software for every field from social upliftment to banking, working on projects throughout Africa and considers herself a polyglot. Her current project involves training and deploying deep learning system to perform a variety of NLP tasks for real life systems - from training the models, to scaling them in production. In her free time, she does ML research on Neural Machine Translation for African languages. Twitter: @alienelf
"Machine Learning Plumbing"
Thanks to the openness of the machine learning community, anyone with a serious 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.