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Ubuntu Blog: Introducing Data Science Stack: set up an ML environment with 3 commands on Ubuntu
- Canonical has released its out-of-the-box Data Science Stack (DSS), which is free to use, fully open source and compatible with Ubuntu, other Linux distributions and Windows Subsystem Linux (WSL).
- DSS enables data scientists to create machine learning (ML) environments with just three commands, allowing for quick initial exploration on AI workstations.
- Canonical provides security maintenance for all the packages included in the DSS, ensuring timely vulnerability patching and protection for the created artefacts.
- The tool includes access to Jupyter Notebook, MLflow and frameworks like Pytorch and Tensorflow.
- McKinsey's research shows 51% of businesses using AI view cybersecurity as the highest risk to mitigate, while 36% view regulatory compliance as a greater risk.
- DSS streamlines AI development and offers a consistent architecture for the process, enabling organisations to mitigate security risks when using containers and open source tools from different sources.
- AI workstations are key for computer makers, and DSS allows them to offer a seamless experience on any device, allowing them to diversify the chosen GPU without impeding the user experience.
- AI practitioners can customise DSS and add new libraries based on their project's specific needs.
- Canonical’s ecosystem manager, Chris Schnabel, said DSS takes away the burden of managing package dependencies or setting up compute resources, and is useful for trained practitioners to get familiar with tools they can use for large-scale ML environments.
- Ubuntu is the most adopted Linux distribution used by AI/ML practitioners for their projects, according to a StackOverflow report, and organisations can purchase security maintenance and support through Ubuntu Pro.
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