Machine Learning workloads on Amazon SageMaker
Amazon SageMaker is a fully managed service that provides every developer and data scientist with the ability to build, train, and deploy machine learning (ML) models quickly. SageMaker removes the heavy lifting from each step of the machine learning process to make it easier to develop high quality models.
Traditional ML development is a complex, expensive, iterative process made even harder because there are no integrated tools for the entire machine learning workflow. You need to stitch together tools and workflows, which is time-consuming and error-prone. SageMaker solves this challenge by providing all of the components used for machine learning in a single toolset so models get to production faster with much less effort and at lower cost.
This tutorial is organised in two sessions, a technical talk on June 9th and a hands-on session on June 10th: in the tech talk, we will explain how Amazon SageMaker works, including a demo. In the lab session, you will get hands-on with Amazon SageMaker features via the CloudBank portal using CERN Single-Sign-On.
Please make sure you register and specifically sign up for the second day with your CERN email address, if you wish to take part in the hands-on training as there is a limited number of places. They will be assigned on a " first come first served" basis.
Please note that we will not use Zoom for remote connection.
Conference call details using AWS Chime for June 9th have been sent to registered participants.
As the tutorial is managed by CloudBank, detailed information about how to access the hands-on will also be made available on this page.