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Hands-On Machine Learning with Azure

You're reading from   Hands-On Machine Learning with Azure Build powerful models with cognitive machine learning and artificial intelligence

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Product type Paperback
Published in Oct 2018
Publisher Packt
ISBN-13 9781789131956
Length 340 pages
Edition 1st Edition
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Authors (6):
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Jen Stirrup Jen Stirrup
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Jen Stirrup
Ryan Murphy Ryan Murphy
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Ryan Murphy
Anindita Basak Anindita Basak
Author Profile Icon Anindita Basak
Anindita Basak
Thomas K Abraham Thomas K Abraham
Author Profile Icon Thomas K Abraham
Thomas K Abraham
Parashar Shah Parashar Shah
Author Profile Icon Parashar Shah
Parashar Shah
Lauri Lehman Lauri Lehman
Author Profile Icon Lauri Lehman
Lauri Lehman
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Table of Contents (14) Chapters Close

Preface 1. AI Cloud Foundations FREE CHAPTER 2. Data Science Process 3. Cognitive Services 4. Bot Framework 5. Azure Machine Learning Studio 6. Scalable Computing for Data Science 7. Machine Learning Server 8. HDInsight 9. Machine Learning with Spark 10. Building Deep Learning Solutions 11. Integration with Other Azure Services 12. End-to-End Machine Learning 13. Other Books You May Enjoy

Machine Learning Server

Microsoft ML Server and its capabilities in SQL Server and HDInsight are the subject of this chapter. In addition, the chapter will provide a walk-through on ML Server's use in order to demonstrate optimal situations in which to use it and how to deploy a solution with it.

Classified algorithms are supervised learning algorithms, which means that they make predictions based on a set of examples.

Often, it is useful to use data to predict a category, and this is known as classification. Take, for example, Andrew Ng's work on the classification of YouTube content as a cat video, or a video of something that is not a cat. As in the famous work by Andrew Ng, when there are only two choices, it is called two-class or binomial classification. When there are more categories, this problem is known as multi-class classification. Multi-class classification...

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