Watch this webinar hosted by Anyscale, the company behind Ray, the unified framework for scalable computing, and Prefect, the modern data workflow and observability for your data science. Learn how Ray and Prefect combine to provide orchestration and observability for your data workflow at any scale easily, and hear a live case study from LiveEO, the satellite based infrastructure monitoring service, on how they use Prefect and Anyscale to streamline their workloads for their customers.

Learn about key aspects of ML scaling:

• Bridge the gap between development and production
  Understand how to scale ML workloads from your laptop to the cloud with no code changes. With a single script prepare data, tune, train and scale your workloads.

• Scale across multiple dimensions
  Hear how organizations are benefitting from embarrassingly parallel experiments and scaling across multiple cores, nodes, and data sources

• Increase developer velocity and speed experimentation
  See how to speed model development and iterations without scaling complexity. Visualize, optimize, collaborate and standardize models and data pipelines.

• Orchestration as a service
  Operationalize, automate and manage your workflows without having to worry about moving your data.

• Coordination plane
  Increase visibility across all of your data and ML workflows.