Domino handles the DevOps so they can focus on delivering quality work.”ĭomino’s integration with MLflow simplifies machine learning lifecycle management for data scientists. “With Domino, our users spin up Ray clusters on demand when needed. “Ray is the ideal distributed processing option to scale machine learning, however it requires DevOps cycles to provision and manage a dedicated cluster for Ray jobs, which you pay for even while it sits idle between distributed training jobs,” said Till Buchacher, Head of Data Science at Direct Line Group. The integration with Domino’s on-demand, auto-scaling compute clusters streamlines the development process, while also supporting data preparation via Apache Spark and machine learning and deep learning via XGBoost, TensorFlow, and PyTorch. Domino now supports version 2.0 of the Ray open-source framework, which enables data science teams to rapidly develop and train generative AI models at scale, including ChatGPT.
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