Machine Learning Runtime
Ready-to-use and optimized machine learning environment
The Machine Learning Runtime (MLR) provides data scientists and ML practitioners with scalable clusters that include popular frameworks, built-in AutoML and optimizations for unmatched performance.
Benefits
Frameworks of Choice
ML Frameworks are evolving at a frenetic pace and practitioners need to manage on average 8 libraries. The ML Runtime provides one-click access to a reliable and performant distribution of the most popular ML frameworks, and custom ML environments via pre-built containers.
Augmented Machine Learning
Accelerate machine learning from data prep to inference with built-in AutoML capabilities including hyperparameter tuning and model search using Hyperopt and MLflow.
Simplified Scaling
Go from small to big data effortlessly with an auto-managed and scalable cluster infrastructure. The Machine Learning Runtime also includes unique performance improvements for the most popular algorithms as well as HorovodRunner, a simple API for distributed deep learning.
Features
How it works
The Machine Learning Runtime is built on top and updated with every Databricks Runtime release. It is generally available across all Databricks product offerings including: Azure Databricks, AWS cloud, GPU clusters and CPU clusters.
To use the ML Runtime, simply select the ML version of the runtime when you create your cluster.
