Manage Your Machine Learning Lifecycle with Azure Databricks

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New KB articles published for the week ending 17th November,2019
November 19, 2019
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November 20, 2019

Machine learning development has new complexities beyond software development. A myriad of tools and frameworks can make it difficult to track experiments, reproduce results, and deploy machine learning models.

Register for this webinar to learn how to accelerate and manage your end-to-end machine learning lifecycle with Azure Databricks–using MLflow and Azure Machine Learning to build, share, deploy, and manage machine learning applications.

Find out how to:

  • Build machine learning experiments using MLflow and Azure Machine Learning.
  • Deploy machine learning models built using Azure Databricks and Azure Machine Learning.

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