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Data Science Workbench

One unified environment to research, experiment collaborate, manage and deploy data science

Unified Code-first Data Science Stack

The Data Science Workbench is a unified code-first environment built by data scientists, for data scientists. cnvrg.io’s data science workbench is the only solution to unify code, projects, and supports deployment at scale. Enhance productivity with container-based model management, MLOps automation, and end to end tracking and monitoring for easy reproducibility.

Accelerate Data Science Workflows with MLOps Automation

  • Simplify engineering heavy tasks like tracking, monitoring, configuration, compute resource management, serving infrastructure, feature extraction, and model deployment
  • Spin up a data science workbench using any language, package or environment
  • Launch pre-configured workspaces with any on-premise, cloud or hybrid compute engine and instantly scale with native Kubernetes, and Spark
  • Rapidly run hundreds of experiments, data science workloads and pipelines simultaneously
workspace-start

Extend Flexibility and Scalability with Custom Interactive Workspaces

  • Data scientists can research and experiment freely with full traceability in one unified interactive workspace
  • Launch any interactive workspace environment with built-in support to Jupyter, RStudio, VSCode, and more with pre-installed dependencies and version control
  • Dynamically attach data, sync files and artifacts with continuous tracking of work
  • Centralize info, logs and metadata with easy access to TensorBoard, SparkUI and all your favorite tools with one data science platform
  • Deploy production-grade endpoints directly from your workspace environment

Improve Productivity with Collaborative Notebooks, Models and Dashboards

  • Track, visualize and share all data science notebooks in your workspace automagically
  • Share and reuse data science components to build fast, reproducible data science workflows
  • Enable end to end model management with hyperparameter optimization, experiment tracking, comparing
  • Quickly publish interactive dashboards using Dash, Voila, or RShiny for improved reporting