Build and deploy PyTorch models with Azure Machine Learning

With machine learning becoming more and more an engineering problem the need to track, work together and easily deploy ML experiments with integrated CI/CD tooling is becoming more relevant then ever.

In this session we take a deep-dive into Azure Machine Learning service, a cloud service that you can use to track as you build, train, deploy, and manage models. We zoom into the building blocks provided and show, through some demos, how to use them.

At the end of this session you have a good grasp of the technological building blocks of Azure machine learning services. Just waiting to be used in your own projects afterwards.