Deep Learning at Scale with PyTorch, Azure Databricks, and Azure Machine Learning

April 9, 2020 10:00 PT

PyTorch is a popular open source machine learning framework. PyTorch is ideal for deep learning applications such as computer vision and natural language processing. MLflow is an open source platform for the end-to-end machine learning lifecycle. Delta Lake is an open source storage layer that brings reliability to data lakes. Azure Databricks is the first-party Databricks service on Azure that provides massive scale data engineering and collaborative data science. Azure Machine Learning Enterprise-grade machine learning service to build and deploy models faster.

Join Databricks and Microsoft as we share how you can easily scale your single-node PyTorch deep learning models using Azure Databricks and Azure Machine Learning. We will show how Azure Databricks enables you to optimize your models by performing many training jobs in parallel without having to make significant changes. Once you have tuned your model, we will show how you can easily put it into production as a web service for applications. We will also show how you can detect and correct model drift over time using MLflow and Delta Lake. See how the right combination of services, integrated in the right way, makes all the difference!

In this webinar you will learn how to:

• Scale your single-node PyTorch deep learning models with Azure Databricks
• Distribute deep learning file reads and writes with local file APIs and Azure Storage
• Leverage Delta Lake to scale file processing from thousands to millions
• Ingest data streams to score live data instead of batch scoring static datasets
• Accelerate deep learning with GPU-accelerated Azure Databricks compute
• Deploy models into production with Azure Machine Learning

Featured Speakers

• Joel Thomas, Sr. Solutions Architect, Databricks
• Felix Schaumann, Applied AI Engineer, T4G
• Hosted by: Clinton Ford, Sr. Partner Marketing Manager, Databricks

Event Sponsor: Databricks (Databricks Privacy Policy)
Event Co-Sponsor: Microsoft Corporation (Microsoft Privacy Statement)