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Deploying and Managing Models in Microsoft Azure

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.

Axel Sirota - Pluralsight course - Deploying and Managing Models in Microsoft Azure
Axel Sirota
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.

Table of contents

About the author
Axel Sirota - Pluralsight course - Deploying and Managing Models in Microsoft Azure
Axel Sirota

Axel Sirota has a Masters degree in Mathematics with a deep interest in Deep Learning and Machine Learning Operations. After researching in Probability, Statistics and Machine Learning optimization, he is currently working at JAMPP as a Machine Learning Research Engineer leveraging customer data for making accurate predictions at Real Time Bidding.

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