About the webinar

We’ve all heard the anecdotes of data scientists spending more time on tooling than ML models. There is no smoke, without fire, right? The truth is AI/ML practitioners struggle with their environments for various reasons, including tooling fragmentation, package dependencies and access to computing power.

There is a wide range of open source tooling that people can choose from. From the operating system to the cloud-native applications, it’s possible to run a fully open source stack to develop your ML models – but how can you do so in an integrated, straightforward way?

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 optimize models without spending time on the necessary underlying tooling. It is designed to run on any AI workstation that runs Ubuntu, maximizing the GPU’s capability and simplifying its usage.

If you’re wondering:

• What does it look like?
• How do you access it?
• What are the minimum requirements to use it?

Then you’re asking the right questions.

Join us to learn about Data Science Stack

Join us in our next webinar 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 & MLOps Product Manager, will talk about:

• Key considerations when getting started with data science
• Data science through the open source lens
• 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 for data science and ML projects on Ubuntu.