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Build Optimal Models with Azure Automated ML

Regardless of if you have some hours or some years building models, Azures’s Automated Machine Learning has something to amaze you. This course will teach you how to use it to build the best Machine Learning model for your data in just a few clicks!

Intermediate
1h 15m
(9)

Created by Axel Sirota

Last Updated Aug 22, 2024

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  • Course

Build Optimal Models with Azure Automated ML

Regardless of if you have some hours or some years building models, Azures’s Automated Machine Learning has something to amaze you. This course will teach you how to use it to build the best Machine Learning model for your data in just a few clicks!

Intermediate
1h 15m
(9)

Created by Axel Sirota

Last Updated Aug 22, 2024

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What you'll learn

Building Machine Learning models means iterating multiple times over the best features, the best architectures, the best algorithms, until you get a model that serves your business purpose. In this course, Build Optimal Models with Azure Automated ML, you’ll learn to create the best machine learning model for your own specific data in just a few clicks. First, you’ll explore what Auto ML really is. Next, you’ll discover how to create optimal models both from the UI as well as the SDK. Finally, you’ll learn how to improve our models with more advanced techniques Azure ML offers. When you’re finished with this course, you’ll have the skills and knowledge of Automated Machine Learning needed to build the best Machine Learning model for your data in just a few clicks!

Build Optimal Models with Azure Automated ML
Intermediate
1h 15m
(9)
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About the author
Axel Sirota - Pluralsight course - Build Optimal Models with Azure Automated ML
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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