How to set-up and execute Kubeflow pipelines through DKube's JuypterLab notebook and how to manage or automate the pipeline runs through the UI. This is one of the hottest features of Kubeflow allowing you to set-up a multi-stage pipeline of data prep, feature engineering, training, and production deployment based on time triggers or other event triggers.
How to launch hyperparameter tuning runs taking advantage of the Katib based hyperparameter tuning available in Kubeflow. Pick the best model from the multiple training runs as the winner based on pre-set criteria.
Want to learn how to monitor your models in production? The DKube platform integrates model monitoring into the overall system with DKube Monitor. It includes everything necessary for engineers and executives to identify how well your models are achieving their business goals - and facilitates a smooth workflow to improve them when necessary.
How to launch a single model training or data preprocessing run through the DKube UI while passing new parameters to pass to the training program via the UI and designated environment variables. Learn how to track the performance characteristics and the lineage of the run with the dataset and model versions used or created in the process.