We are happy to announce that Data Science Stack is now available in Beta. It is a foundation part of Ubuntu AI ecosystem, enabling users to quickly get started with data science or machine learning on their workstation.
What is Data Science Stack?
Data Science Stack (DSS) is an out-of-the-box solution for data scientists and machine learning engineers, published by Canonical. It is a ready-made environment for ML enthusiasts that enables them to develop and optimise models without spending time on the necessary tooling. It is designed to run on any Ubuntu AI workstation, maximising the GPU’s capability and simplifying its usage. Are you curious?
Our documentation includes a tutorial, a list of how-to guides, and some further explanations to make it easier for you. Take a look here.
Join our webinar to talk about data science tools
Join us in our next webinar on [date] to learn more about data science tools, with a focus on DSS and its capabilities. During the webinar, Michal Hucko, MLOps engineer at Canonical and Andreea Munteanu, AI Product Manager, will talk about:
- Key considerations when getting started with data science
- Data science through the open source lenses
- Deep dive into Data science stack (DSS)
- Demo of the DSS
Prepare your questions and join us live to get insights into how DSS improves the developer experience of Ubuntu users who are active in the data science or ML space.
Don’t be shy. Share your feedback.
The Data science stack is a developer tool that can only evolve with the care, time and feedback that our community gives. We would like to hear more from you. You should let us know about:
- Issues you might face during the installation
- Uncertainties while following our documentation
- Blockers you have to use DSS
- Improvement opportunities of the tool
- Questions about the solution
Contribute directly to our GitHub and join our online chat on Matrix.
Please be mindful that this is an inital version of the tool, so there is always a risk that something might go wrong. Save your work to proceed with caution. If you encounter any difficulties, our team is here to hear your feedback and help you. Since this is a Beta version, Canonical does not recommend running or upgrading it in any production environment.