Scaling data processing and ML workloads with AWS (Level 200)

Building scalable data and AI and machine workloads is a cross-team effort that requires management of several resources. The lack of proper management results in teams having to spend significant time on operational tasks, which slows down time-to-market, and keeping them from focusing on developing innovative products and solutions. In this session, we outline the options to scale complex data and AI/ML workloads on AWS. Learn how Amazon SageMaker Pipelines brings CI/CD pipelines to ML, reducing the months of coding previously required to just a few hours. Uncover other options on how to deploy best-of-breed open source machine learning systems on AWS, enabling developers, data scientists and builders with the right tools to run machine learning on the cloud. Download slides »
Speaker: Vatsal Shah, Senior Solutions Architect, AWS India
Duration: 30mins