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Choosing the Appropriate Microsoft Azure Services and Features

by James Bannan

This course will set the scene for understanding the different Azure services which are available to enable and support AI solutions and how to map business requirements in order to arrive at the right recommendations for your data teams.

What you'll learn

AI solutions in Microsoft Azure consist of a number of independent resources and services working together holistically to produce a complex solution. As an AI Engineer, In this course, Choosing the Appropriate Microsoft Azure Services and Features, you’ll gain understanding of the processes which are inherent within an AI solution as well as some of the challenges faced by data scientists in the building and training of machine learning models in order to be able to recommend the most appropriate services and features. First, you’ll look at the different types of data that you’re going to need to understand and deal with, including recommending the right services to support different data scenarios. Then, you’ll explore the difference between machine learning models and frameworks, including the different types of machine learning models, incorporating both standard machine learning as well as deep learning. Finally, you’ll explore machine learning pipelines and automated machine learning, including the business and technical challenges that these technologies are designed to overcome. At the end of this course, you will have a basic understanding of the different Azure services.

About the author

James Bannan is a consultant based in Melbourne, Australia. He has worked in the IT industry for over 18 years and has worked in a variety of roles, from helpdesk to systems administration and now as a consultant. He is a published author, having written many articles for both print and online publications as well as a book on System Center Configuration Manager. James is an experienced public speaker and was awarded the Most Valuable Professional (MVP) award from Microsoft for eight years in a ... more

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