AI, ML, & Ubuntu: Everything you need to know
Canonical
on 26 July 2018
Tags: AI , AI/ML , GPGPU , Kubeflow , kubernetes , ML , MLOps , TensorFlow , Ubuntu
AI and ML adoption in the enterprise is exploding from Silicon Valley to Wall Street. Ubuntu is the premier platform for these ambitions — from developer workstations, to racks, to clouds and to the edge with smart connected IoT. One of the joys that come with new developer trends are a plethora of new technologies and terminologies to understand.
In this webinar, join Canonical’s Kubernetes Product Manager Carmine Rimi for:
- An introduction to some of the key concepts in Machine Learning
- A look into some examples of how AI applications and their development are reshaping company’s IT
- A deep dive into how enterprises are applying devops practices to their ML infrastructure and workflows
- An introduction to Canonical AI / ML portfolio from Ubuntu to the Canonical Distribution of Kubernetes and and how to get started quickly with your project
And in addition, we’ll be answering some of these questions:
- What do Kubeflow, Tensorflow, Jupyter, and GPGPUs do?
- What’s the difference between AI, ML and DL?
- What is an AI model? How do you train it? How do you develop / improve it? How do you execute it?
And finally, we’ll be taking the time to answer your questions in a Q&A session
Enterprise AI, simplified

AI doesn’t have to be difficult. Accelerate innovation with an end-to-end stack that delivers all the open source tooling you need for the entire AI/ML lifecycle.