Out of the box spins up a full-fledged ML development environment with all the tools you need at your fingertips. If you don’t see something you want in the table, you will probably find it here: Awesome Production Machine Learning. Let us know, and we’ll add it to your deployment

  • All tools are open-source
  • All tools are installed in the same cluster
  • CV and NLP projects on Python
  • AWS, GCP, or Azure
#ML project lifecycle componentTool
1Data labeling Label Studio
2Data management DVC
3Development environmentVSCode and Jupyter 
4Remote debuggingVSCode remote debugger
5Code managementGit
6Experiment trackingMLflow
7Hyperparameter tuningNNI
9Metadata managementMLflow
10Model managementMLflow
11DeploymentSeldon Core
13MonitoringPrometheus + Grafana
14InterpretationSeldon Alibi
17Access control orchestration can save a team of five data scientists over $100,000 per year: Check out the online calculator