Innovative and Reproducible​

Remove barriers to innovation and instill confidence in the integrity of data-driven analyses.

Environment Management​

Ensure analyses and experiments are executed in a consistent and reproducible environment.​

Version Control

Trace the evolution of analytical methods and models to accurately reproduce experiments.​

Documentation and Collaboration​

Centralize code collaboration, explanations, and visualizations.​

Containerization

Package code, data, and dependencies into portable containers.​

Package Consistency

Use tested and compatible versions of packages.​

Resources

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8 Levels of Reproducibility: Future-Proofing Your Python Projects
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Anaconda Learning: Turbocharge your Python Journey in Anaconda Notebooks
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Build and Deploy Data Apps in Anaconda Notebooks

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