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KernelQuad

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Browser-based data science workspaces provide universities, instructors, students, and analyst teams with ready-to-use Python, R, and SQL environments, shared GPUs, JupyterLab and VS Code support, and templates for tools such as PyTorch, TensorFlow, and Spark. They simplify course setup, eliminate inconsistent local installations, control cloud spending with hard budgets and automatic shutdowns, let campus hardware scale into the cloud, and keep notebooks and data in a selected region.

KernelQuad can be found in Data Science Notebooks & Platforms categories.

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