Using MLflow with Databricks

MLflow in a leading framework for MLOps supporting the tracking, registry and deployment of Machine Learning models. In this course, we'll teach how to use MLflow end-to-end using Azure Databricks.

Agenda

In this 1-day course you'll learn what MLflow is and how to use it in Azure Databricks. We'll cover

  • MLflow set-up: we'll learn you how to set-up MLflow in Databricks using all best-practices 
  • MLflow tracking: learning you how to track and record different training runs & performance parameters during your various model runs
  • Discuss deployment options of Machine Learning incl. batch, streaming, and real-time use cases and how MLflow and Azure ML fit into the mix
  • MLflow deployment: learning you to register a model, deploy that model into production & update a model in production to new version including a staging phase for testing
  • MLflow administration and CICD using Azure ML: learning you how to administrator MLflow rights, access and a CICD-way-of-working using Azure DevOps and Mlflow 

Using MLflow with Databricks

Audience

Cost

  • € 675 per day

Interested to know more?

For more information, please reach out academy@element61.be and we can give you more details & practicals.

The full element61 Training schedule (incl. when which training runs) can be found here.

Using MLflow with Databricks

For a complete overview of all courses, visit our academy page.