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Introducing Microsoft SQL Server 2019

You're reading from   Introducing Microsoft SQL Server 2019 Reliability, scalability, and security both on premises and in the cloud

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Product type Paperback
Published in Apr 2020
Publisher Packt
ISBN-13 9781838826215
Length 488 pages
Edition 1st Edition
Languages
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Authors (8):
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Allan Hirt Allan Hirt
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Allan Hirt
Dustin Ryan Dustin Ryan
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Dustin Ryan
Mitchell Pearson Mitchell Pearson
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Mitchell Pearson
Kellyn Gorman Kellyn Gorman
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Kellyn Gorman
Dave Noderer Dave Noderer
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Dave Noderer
Buck Woody Buck Woody
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Buck Woody
Arun Sirpal Arun Sirpal
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Arun Sirpal
James Rowland-Jones James Rowland-Jones
Author Profile Icon James Rowland-Jones
James Rowland-Jones
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Table of Contents (15) Chapters Close

Preface 1. Optimizing for performance, scalability and real‑time insights 2. Enterprise Security FREE CHAPTER 3. High Availability and Disaster Recovery 4. Hybrid Features – SQL Server and Microsoft Azure 5. SQL Server 2019 on Linux 6. SQL Server 2019 in Containers and Kubernetes 7. Data Virtualization 8. Machine Learning Services Extensibility Framework 9. SQL Server 2019 Big Data Clusters 10. Enhancing the Developer Experience 11. Data Warehousing 12. Analysis Services 13. Power BI Report Server 14. Modernization to the Azure Cloud

8. Machine Learning Services Extensibility Framework

"Data science" is the broader term given to data analysis techniques done in a scientific manner: create a hypothesis, create a test of the hypothesis, and validate the results (most often with a peer review). It involves standard data analysis techniques, such as queries, reports, and data exploration using business intelligence, and goes further by setting up tests using statistical and algorithmic tools for machine learning.

In this chapter, you'll briefly explore machine learning, the components and architectures in SQL Server 2019 you can use to implement these services, and a process you can follow to include them in a solution. You'll learn the new features in SQL Server 2019 for machine learning platform.

You'll start with a quick overview of machine learning, and then move on to working with the tools to create predictive models and classification. You'll then move on to installing...

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