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Hands-On Data Science with SQL Server 2017

You're reading from   Hands-On Data Science with SQL Server 2017 Perform end-to-end data analysis to gain efficient data insight

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Product type Paperback
Published in Nov 2018
Publisher Packt
ISBN-13 9781788996341
Length 506 pages
Edition 1st Edition
Languages
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Authors (2):
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Vladimír Mužný Vladimír Mužný
Author Profile Icon Vladimír Mužný
Vladimír Mužný
Marek Chmel Marek Chmel
Author Profile Icon Marek Chmel
Marek Chmel
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Toc

Table of Contents (14) Chapters Close

Preface 1. Data Science Overview FREE CHAPTER 2. SQL Server 2017 as a Data Science Platform 3. Data Sources for Analytics 4. Data Transforming and Cleaning with T-SQL 5. Data Exploration and Statistics with T-SQL 6. Custom Aggregations on SQL Server 7. Data Visualization 8. Data Transformations with Other Tools 9. Predictive Model Training and Evaluation 10. Making Predictions 11. Getting It All Together - A Real-World Example 12. Next Steps with Data Science and SQL 13. Other Books You May Enjoy

Assignment and preparation

Our real-time example will be used to show some simple predictions made as regression models built at the top of a data gathered by a very small virtual cellphone service provider. We want to estimate how many text messages and voice calls a new customer will make. This will help us to recommend a proper prepaid service plan to the new customer.

Our prediction will be based on the knowledge that we will put into our predictive model. The results of the prediction will be very approximate because the amount of data is rather small and the model will also have a very limited set of input parameters.

Before we start to develop anything, we will need to set up a basic environment. The following section will briefly suggest the necessary configurations for the success of our project.

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