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Data Science with SQL Server Quick Start Guide

You're reading from   Data Science with SQL Server Quick Start Guide Integrate SQL Server with data science

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Product type Paperback
Published in Aug 2018
Publisher Packt
ISBN-13 9781789537123
Length 206 pages
Edition 1st Edition
Languages
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Author (1):
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Dejan Sarka Dejan Sarka
Author Profile Icon Dejan Sarka
Dejan Sarka
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Table of Contents (10) Chapters Close

Preface 1. Writing Queries with T-SQL FREE CHAPTER 2. Introducing R 3. Getting Familiar with Python 4. Data Overview 5. Data Preparation 6. Intermediate Statistics and Graphs 7. Unsupervised Machine Learning 8. Supervised Machine Learning 9. Other Books You May Enjoy

Supervised Machine Learning

In Chapter 6, Intermediate Statistics and Graphs, we read about intermediate statistics with linear regression. I will continue this chapter from that point. Linear regression is already an algorithm you can use for predictions. You can make predictions with the directed, or the supervised, algorithms. Supervised algorithms have a target, or a dependent variable. They try to explain the values of that variable with the formula and the values of the independent variables. This explanation is stored in a model, which you use to predict the target variable value on a new dataset. The dependent variable supervises the development of the model. In a real project, you create many models, and then you deploy the one that suits your business needs the best. Therefore, you need to evaluate the models before the deployment.

In this chapter, I will...

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