SKIL Documentation

The Skymind Platform

SKIL Community Edition (SKIL CE) gives developers an easy way to train and deploy powerful deep learning models to production environments quickly and easily.

SKIL CE is a free, on-premise, AWS-like platform for machine learning, where data scientists and data engineers can use an open-source stack of machine learning and big data tools. It enables a managed Spark/GPU cluster as well as a managed AI model server for experiment tracking and model deployment, accessible through notebooks and a GUI. The platform is extensible, like a job runner for machine learning apps.

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Release Notes

New Features and Changes in SKIL v1.0.2

  • Multi-node SKIL installations for inference are now supported
  • Completely offline installable RPMs
  • Added display names for processes
  • Ability to customize the configuration of the default zeppelin server
  • Configurable Logging
  • Many small UI and usability improvements

Known Issues in SKIL v1.0.2

  • Stopping a deployment can cause temporary errors in workspaces. Simply trying the action again should get rid of the error.
  • Currently not possible to delete a model with attached Evaluation Results from an Experiment.
  • The embedded Zookeeper in SKIL stores data in-memory and restarting the SKIL server will cause errors in Workspaces and deployments. Use of an external Zookeeper is recommended.

Release Notes