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Deploying Models with Azure Machine Learning

This course will teach you how to navigate the Azure ML platform, create a workspace, find and fine-tune models, deploy it, and perform high-level fairness and interpretability assessments.

Beginner
17m
(4)

Created by Axel Sirota

Last Updated Jul 15, 2024

Course Thumbnail
  • Course

Deploying Models with Azure Machine Learning

This course will teach you how to navigate the Azure ML platform, create a workspace, find and fine-tune models, deploy it, and perform high-level fairness and interpretability assessments.

Beginner
17m
(4)

Created by Axel Sirota

Last Updated Jul 15, 2024

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This course is included in the libraries shown below:

  • AI
  • Cloud
What you'll learn

Navigating the world of machine learning can be challenging, especially for beginners. In this course, Deploying Models with Azure Machine Learning, you’ll learn to effectively utilize the Azure ML platform to build, deploy, and assess machine learning models. First, you’ll explore the core components of Azure ML, including workspaces, compute resources, and data stores. Next, you’ll discover how to find and fine-tune models using the model catalog and conduct experiments with custom datasets. Finally, you’ll learn how to deploy these models and perform high-level fairness and interpretability assessments to ensure ethical AI practices. When you’re finished with this course, you’ll have the skills and knowledge of Azure Machine Learning needed to confidently build, deploy, and assess machine learning models on the Azure platform.

Deploying Models with Azure Machine Learning
Beginner
17m
(4)
Table of contents

About the author
Axel Sirota - Pluralsight course - Deploying Models with Azure Machine Learning
Axel Sirota
36 courses 3.6 author rating 1141 ratings

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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