Machine Learning (ML) opens up unparalleled opportunities for organizations around automation, efficiency, and innovation. In order to take full advantage of this technology, you must ensure you’re following best practices for building reliable, secure, and cost-effective ML workloads. As an AWS Premier Consulting Partner with the Machine Learning Competency, ClearScale can help you design, deploy, and architect your ML workloads on AWS.
Based on an assessment of your ML applications using five pillars of evaluation - operational excellence, security, reliability, performance efficiency, and cost optimization - ClearScale will cover AWS best practices in the context of:
- AI services
- Managed ML services
- ML frameworks on AWS
We’ll use these best practices, composed as a set of questions, to review your existing or proposed ML workloads. At the end of this free evaluation, you’ll come away with guidance on how you can build and operate reliable, secure, efficient, and cost-effective ML workloads in the AWS cloud.
Fill out this short form and we’ll get started.