Amazon SageMaker and Open-Source Tools for ML: Better Together
Looking to explore the capabilities of fully managed AWS services in combination with open-source tools? Come learn from Provectus and start using Amazon Sagemaker mixed and matched with the best open-source services for ML!
During the hands-on workshop, Provectus experts will walk you through the steps required for designing and building a customizable, highly scalable ML Infrastructure based on Amazon SageMaker and open-source components. We will discuss pros and cons, the limitations of different tools that support specific stages of the ML workflow, and best practices for MLOps, to automate these stages into repeatable pipelines.
Agenda
Overview of Modern ML Infrastructure on AWS combined with open-source components
Real-world case study on building ML Infrastructure for Vision Screening with Amazon SageMaker and Kubeflow
Hands-on walk-through demo of the complete ML Engineer Experience — ML Lifecycle: From Data to ML Model Deployment and Retraining
Schedule a 30-minute pre-assessment session for ML Acceleration Program https://provectus.com/ml-infrastructu...
The program is fully funded by Provectus and AWS and available to selected customers upon qualification.
Intended Audience
DevOps & Infrastructure teams, ML Engineers, MLOps professionals, and Architects.
Presenters
Rinat Gareev, ML Solutions Architect at Provectus
Dmitrii Evstiukhin, Senior Solutions Architect at Provectus
Lenar Gabdrakhmanov, ML Engineer at Provectus