MLRun version 0.7.0 and 0.7.1 are now generally available. These releases includes the following:  Automate the model monitoring deployment Support ingestion of deltas for a scheduled feature set Add a new wizard for creating an MLRun function Usability enhancements around working with projects, function , volume mounts, pipeline etc.. Fixed window returns the last closed window

MLRun version 0.6.5 is now generally available. The release includes the following:  Supports node selectors when running a new job Feature Store updates:    Improved ingestion and aggregation logic and performance    Model UI now includes information about the feature vector Kubernetes secrets provider is now supported Enables mpijob as an MLRun runtime Additional logging capabilities of PyTorch...

Take a look at a few of the inspiring projects from our first-ever hackathon: ICU-OPS: Help frontline clinicians triage patients in ICUs by rapidly assessing a patient’s overall health for informed clinical decisions that will improve patient outcomes and relieve COVID19 ICU overload. Deepfake Shield: Fighting deepfakes with deep-learning. COVID-19 Detection through Radiography images of...

Check out the latest release of MLRun, with several new features and enhancements. Feature store updates: Parquet partitioning is now supported Read offline data with time range Data ingestion using Spark Reduce the docker images size for faster delivery over the network A new CLI option to submit functions/projects to the cluster Deploy model via...

Check out the latest release of MLRun, with updates to the feature store, and more functionality from the UI. Feature store updated: Support for multiple ingestion engines: Pandas, Spark, Storey Ingestion now supports filtering by date Feature sets now include code usage examples Model monitoring has been improved and now includes feature analysis and drift...