For customers who have yet to deploy their first ML workload on AWS, we bring clarity to topics such as:

What impact AI/ML could deliver for their business

How to set up scalable and reliable data pipelines

How to show results from AI/ML projects more quickly with existing resources

How to support your entire data journey, from data lake migration to building and deploying your first ML model to running ML reliably at scale

For customers who are looking to expand their ML footprint, we advise and guide on topics such as:

How to improve reliability and scalability of existing models

How to set up custom ML pipelines and automation to serve your unique scenario

Where AWS ML services, GPU-optimization instance types and big data processing services best match your use case

How to use services like Amazon SageMaker to drive new innovations, faster