Machine Learning Deployments on Kubernetes | Ed Shee

Until recently, the Data Science and Machine Learning (ML) field has been under utilised in its adoption of DevOps tools and processes However that's now changing, as engineering teams gain any value from their Machine learning models, by get them into production. In this talk, Ed will introduce the open source Seldon Core library, build a model using popular machine learning tools and deploy it to Kubernetes to handle production traffic. You will learn how to turn an ML model into a production microservice that handles REST/gRPC traffic, how to use complex model deployment techniques and how to monitor both the infrastructure and the models themselves, spotting drift and outliers as they take place.