cnvrg.io

Developing, experimenting, and deploying ML models at scale requires substantial tooling, scripting, tracking, versioning, and monitoring. Data scientists want to do data science – and are slowed down by MLOps and DevOps tasks. They lack user friendly tools needed to track experiments, attach resources, manage datasets and launch multiple ML pipelines. In this webinar cnvrg.io…