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Deploying No-Code Automated MLOps for Amazon Forecast - AWS Online Tech Talks

Traditional approaches to deploying Amazon Forecast works required customers to click through the console or learn APIs using Jupyter notebooks. Both of these approaches increase the barrier to ongoing, sustainable production operation at scale. In this session, we will show you how to deploy recurring Amazon Forecast workloads with no-code, using AWS CloudFormation, AWS Step Functions and AWS Systems Manager. This solution provides customers with a consistent, scalable pipeline from Day 1 first-use exploration, to PoC, to production deployments - without a need for refactoring. In addition, the solution helps deploy and manage many decoupled and concurrent workloads. Learning Objectives: Objective 1: Attendees will learn how to generate highly accurate predictions with Amazon Forecast. Objective 2: Attendees will understand the macro level processes of pulling data from various sources, importing, building a model, producing inference, and using time-series predictions to achieve business goals. Objective 3: Attendees will learn how to deploy automated MLOps pipelines to quickly move from PoCs to production. ***To learn more about the services featured in this talk, please visit: https://aws.amazon.com/forecast/ ****To download a copy of the slide deck from this webinar visit: https://pages.awscloud.com/Deploying-... Subscribe to AWS Online Tech Talks On AWS: https://www.youtube.com/@AWSOnlineTec... Follow Amazon Web Services: Official Website: https://aws.amazon.com/what-is-aws Twitch:   / aws   Twitter:   / awsdevelopers   Facebook:   / amazonwebservices   Instagram:   / amazonwebservices   ☁️ AWS Online Tech Talks cover a wide range of topics and expertise levels through technical deep dives, demos, customer examples, and live Q&A with AWS experts. Builders can choose from bite-sized 15-minute sessions, insightful fireside chats, immersive virtual workshops, interactive office hours, or watch on-demand tech talks at your own pace. Join us to fuel your learning journey with AWS. #AWS