Expanded Library

Deploying and Managing Models in Microsoft Azure

by Axel Sirota

To deliver a great idea, one needs to deploy your ML models as well as ensure they keep up to date. This course will teach you the best practices to deploy, manage, and retrain machine learning models in Azure.

What you'll learn

Once a model is created, we need to deploy it. Moreover, we need to ensure their performance does not decay and we keep track of the current model in production. In this course, Deploying and Managing Models in Microsoft Azure, you’ll learn the best practices to deploy, manage, and retrain machine learning models in Azure. First, you’ll explore how to deploy machine learning models in Azure. Next, you’ll discover how to create a retraining pipeline with Azure ML Pipelines. Finally, you’ll learn about MLOps practices to take into account. When you’re finished with this course, you’ll have the skills and knowledge of machine learning operations in Azure needed to deploy, manage, and retrain machine learning models in Azure.

About the author

Axel Sirota is a Microsoft Certified Trainer with a deep interest in Deep Learning and Machine Learning Operations. He has a Masters degree in Mathematics and after researching in Probability, Statistics and Machine Learning optimisation, he works as an AI and Cloud Consultant as well as being an Author and Instructor at Pluralsight, Develop Intelligence, and O'Reilly Media.

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