RAMP Program is a customer-centered workshop program in which customers directly configure MLOps for automating the model's seamless workflow with AWS' model development environment through the use of hands-on AWS services. RAMP allows customers to experience real-world trial-and-error experiences by using AWS' services themselves, thereby further enhancing their understanding of AWS' services. In addition, RAMP can be used as a base architecture for future customer actual workloads based on the architecture created in the customer's account.
In the MLOPS RAMP Program, as a Data Scientist, customers develop models in Amazon SageMaker, or you actually do methods of model inference, and in the role of Machine Learning Platform Engineer/MLOps Engineer, you implement the end-to-end workflow from data preparation to model distribution.
This senario performs model development using the Object Detection model of Yolov5 and then builds the MLOps architecture directly using AWS Step Functions from the customer's account. All implementations are directly done by the customer and the issues that arise during the course of the program are shared by the SAs in charge and supported by debugging.
This senario performs model development using the Binary Classification model of Autogluon and then builds the MLOps architecture using SageMaker Pipelines from the customer's account. All implementations are directly done by the customer and the issues that arise during the course of the program are shared by the SAs in charge and supported by debugging.
See CONTRIBUTING for more information.
This library is licensed under the MIT-0 License. See the LICENSE file.