Data Science Workbench

Create a browser-based data science IDE with a notebook interface, integrated AI copilot, visual data exploration, and reproducible experiment tracking. Support Python-like data operations via a JavaScript DSL, GPU-accelerated model training, and one-click deployment of models as REST APIs.

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idedata-sciencenotebookexperiment-tracking

Objectives

Build a notebook interface with executable code cells, markdown cells, and rich output
Implement an AI copilot that suggests code, fixes errors, and explains results inline
Create a visual data exploration panel with automatic profiling and chart suggestions
Add experiment tracking with versioned datasets, parameters, metrics, and artifact storage
Support model deployment as API endpoints with auto-generated documentation

Hints

Use CodeMirror or Monaco Editor for the code cell editor with syntax highlighting
Implement a sandboxed JavaScript execution environment using Web Workers
Track experiments as immutable snapshots with diff capabilities between runs

Resources

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