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Designing Machine Learning Solutions on Microsoft Azure

by David Tucker

This course will cover how to leverage Azure Machine Learning for a successful data science initiative across the key components of workflow, data pipeline, and infrastructure.

What you'll learn

When working on data science initiatives it can be challenging to gain actionable insights from your data set. In this course, Designing Machine Learning Solutions on Microsoft Azure, you will learn how to leverage Azure's Machine Learning capabilities to greatly increase the chance of success for your data science project. First, you will engage in team workflow and how Microsoft's Team Data Science Process (TDSP) enables best practices across disciplines. Next, you will discover the workflow of the Azure Machine Learning Service and how it can be leveraged on your project. After this, you will review how to create a pipeline for your data preparation, model training, and model registration. Finally, you will explore the infrastructure approaches that can be leveraged for machine learning and how those approaches are supported on Azure. When you are finished with this course, you will possess the skills that will be needed to start a data science project on Azure and the tools that will increase your ability to gain those actionable insights.

About the author

David is a Webby Award winning cloud development consultant that focuses on cloud native web, mobile, and IoT applications. For over fifteen years as a consultant David has led custom software development on emerging platforms for companies such as FedEx, AT&T, Sony Music, Intel, Comcast, Herman Miller, Principal Financial, and Adobe (as well as many others). David regularly writes and speaks on the digital landscape with published works for O'Reilly and He has written for Mashable,... more

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