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Building Your First Data Science Project in Microsoft Azure

Behind every machine learning model, there is a great service solving issues like versioning, shareability, deployment, and reproducibility. This course will teach you how to properly start with the right foot on your Data Science projects.

Beginner
1h 51m
(24)

Created by Axel Sirota

Last Updated Aug 22, 2024

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  • Course

Building Your First Data Science Project in Microsoft Azure

Behind every machine learning model, there is a great service solving issues like versioning, shareability, deployment, and reproducibility. This course will teach you how to properly start with the right foot on your Data Science projects.

Beginner
1h 51m
(24)

Created by Axel Sirota

Last Updated Aug 22, 2024

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This course is included in the libraries shown below:

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  • Cloud
  • Data
What you'll learn

Creating a machine learning model in Azure may seem daunting at first. There are a ton of configurations and specifications to take into account. In this course, Building Your First Data Science Project in Microsoft Azure, you’ll learn how to properly start with the right foot on your Data Science projects with Azure Machine Learning. First, you’ll explore what Azure Machine Learning is. Next, you’ll discover how to select and configure your development environment to ensure success. Finally, you’ll learn how to configure deployments and all the deployment targets within Azure. When you’re finished with this course, you’ll have the skills and knowledge of Azure Machine Learning needed to start your Ml projects the right way.

Building Your First Data Science Project in Microsoft Azure
Beginner
1h 51m
(24)
Table of contents

About the author
Axel Sirota - Pluralsight course - Building Your First Data Science Project in Microsoft Azure
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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