Today we are excited to strengthen our commitment to supporting PyTorch as a first-class framework on Azure, with exciting new capabilities in our Azure Machine Learning public preview refresh. In addition, our PyTorch support extends deeply across many of our AI Platform services and tooling, which we will highlight below. During the past two years since PyTorch's first release in October 2016, we've witnessed the rapid and organic adoption of the deep learning framework among academia, industry, and the AI community at large. While PyTorch's Python-first integration and imperative style have long made the framework a hit among researchers, the latest PyTorch 1.0 release brings the production-level readiness and scalability needed to make it a true end-to-end deep learning platform, from prototyping to production. Azure Machine Learning (Azure ML) service is a cloud-based service that enables data scientists to carry out end-to-end machine learning workflows, from data preparation and training to model management and deployment.