What you’ll learn
- The key concepts in Machine Learning
- How AI applications and their development are reshaping company’s IT
- How enterprises are applying devops practices to their ML infrastructure and workflows
- How Canonical’s AI / ML portfolio from Ubuntu to the Charmed Distribution of Kubernetes and and how to get started
quickly with your project
Other questions answered
- 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?