Sustainable and scalable machine learning with Amazon EKS and Argo workflows (Level 200)

Data science, machine learning, artificial intelligence, and Kubernetes have exploded in popularity in the last few years, resulting in organizations focusing on building out dedicated ML teams to help scale the delivery of ML-powered outcomes. As organizations scale the use of these technologies and practices, they face a number of challenges including the reproducibility of model outputs, reusability of pipelines, pipeline versioning, manageability of model deployment, and serving and automation of these end-to-end processes. In this session, we dive deep into how you can build a scalable architecture for ML data preparation, model training, and serving using Argo workflows and Amazon Elastic Kubernetes Services (Amazon EKS). Download slides »
Speaker: Mitch Beaumont, Principal Solutions Architect, AWS
Duration: 30mins