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Data Science with SQL Server Quick Start Guide

Data Science with SQL Server Quick Start Guide

By : Dejan Sarka
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Data Science with SQL Server Quick Start Guide

Data Science with SQL Server Quick Start Guide

4 (1)
By: Dejan Sarka

Overview of this book

SQL Server only started to fully support data science with its two most recent editions. If you are a professional from both worlds, SQL Server and data science, and interested in using SQL Server and Machine Learning (ML) Services for your projects, then this is the ideal book for you. This book is the ideal introduction to data science with Microsoft SQL Server and In-Database ML Services. It covers all stages of a data science project, from businessand data understanding,through data overview, data preparation, modeling and using algorithms, model evaluation, and deployment. You will learn to use the engines and languages that come with SQL Server, including ML Services with R and Python languages and Transact-SQL. You will also learn how to choose which algorithm to use for which task, and learn the working of each algorithm.
Table of Contents (10 chapters)
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Selecting the Python environment

Once you've installed ML Services (in-database), in Chapter 1Writing Queries with T-SQL, and Visual Studio 2017 for data science and analytical applications, in Chapter 2, Introducing R, you need to create the appropriate VS 2017 Python environment. VS 2017 installs the Anaconda Python, an open source Python distribution, that does not include Microsoft libraries. You need to select the Python distribution that comes with SQL Server, ML Services (In-database). There is no need for such a step for R , because VS 2017 also installs Microsoft R Client. As you should remember from Chapter 2, Introducing RMicrosoft R Client is the open R engine distributed by Microsoft, and this version includes the Microsoft scalable libraries.

After you install VS 2017, your default Python environment is Anaconda. You need to add an additional Python...

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