Data Science with SQL Server Quick Start Guide Integrate SQL Server with Data Science

SQL Server started to fully support data science only with its last two editions. If you are a professional from both worlds, SQL Server and data science, and interested in using SQL Server and Machine Learning Services for their projects, then this is the ideal book for you.

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Bibliographic Details
Main Author: Sarka, Dejan
Format: eBook
Language:English
Published: Birmingham Packt Publishing, Limited 2018
Packt Publishing Limited
Packt Publishing
Edition:1
Subjects:
COM018000 COMPUTERS / Data Processing
COMPUTERS / Data Modeling & Design
COMPUTERS / Database Management / Data Mining
Database management
SQL (Computer program language)
ISBN:9781789537123, 1789537126
Online Access:Get full text
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Abstract SQL Server started to fully support data science only with its last two editions. If you are a professional from both worlds, SQL Server and data science, and interested in using SQL Server and Machine Learning Services for their projects, then this is the ideal book for you.
AbstractList SQL Server started to fully support data science only with its last two editions. If you are a professional from both worlds, SQL Server and data science, and interested in using SQL Server and Machine Learning Services for their projects, then this is the ideal book for you.
Author Sarka, Dejan
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1789537126
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Snippet SQL Server started to fully support data science only with its last two editions. If you are a professional from both worlds, SQL Server and data science, and...
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SubjectTerms COM018000 COMPUTERS / Data Processing
COMPUTERS / Data Modeling & Design
COMPUTERS / Database Management / Data Mining
Database management
SQL (Computer program language)
Subtitle Integrate SQL Server with Data Science
TableOfContents Discovering associations between continuous and discrete variables -- Expressing dependencies with a linear regression formula -- Summary -- Chapter 7: Unsupervised Machine Learning -- Installing ML services (In-Database) packages -- Performing market-basket analysis -- Finding clusters of similar cases -- Principal components and factor analyses -- Summary -- Chapter 8: Supervised Machine Learning -- Evaluating predictive models -- Using the Naive Bayes algorithm -- Predicting with logistic regression -- Trees, forests, and more trees -- Predicting with T-SQL -- Summary -- Other Books You May Enjoy -- Index
Cover -- Title Page -- Copyright and Credits -- Packt Upsell -- Contributors -- Table of Contents -- Preface -- Chapter 1: Writing Queries with T-SQL -- Before starting - installing SQL Server -- SQL Server setup -- Core T-SQL SELECT statement elements -- The simplest form of the SELECT statement -- Joining multiple tables -- Grouping and aggregating data -- Advanced SELECT techniques -- Introducing subqueries -- Window functions -- Common table expressions -- Finding top n rows and using the APPLY operator -- Summary -- Chapter 2: Introducing R -- Obtaining R -- Your first line R of code in R -- Learning the basics of the R language -- Using R data structures -- Summary -- Chapter 3: Getting Familiar with Python -- Selecting the Python environment -- Writing your first python code -- Using functions, branches, and loops -- Organizing the data -- Integrating SQL Server and ML -- Summary -- Chapter 4: Data Overview -- Getting familiar with a data science project life cycle -- Ways to measure data values -- Introducing descriptive statistics for continuous variables -- Calculating centers of a distribution -- Measuring the spread -- Higher population moments -- Using frequency tables to understand discrete variables -- Showing associations graphically -- Summary -- Chapter 5: Data Preparation -- Handling missing values -- Creating dummies -- Discretizing continuous variables -- Equal width discretization -- Equal height discretization -- Custom discretization -- The entropy of a discrete variable -- Advanced data preparation topics -- Efficient grouping and aggregating in T-SQL -- Leveraging Microsoft scalable libraries in Python -- Using the dplyr package in R -- Summary -- Chapter 6: Intermediate Statistics and Graphs -- Exploring associations between continuous variables -- Measuring dependencies between discrete variables
Data Science with SQL Server Quick Start Guide: Integrate SQL Server with data science
Title Data Science with SQL Server Quick Start Guide
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