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1
Introduction
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Questions
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Sponsors
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Explore PASS
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About the speaker
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Background
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Why predictive analytics
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Predictive analytics in every industry
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Adoption of predictive analytics
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Reality Bites
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Four Big Challenges
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Three Step Process
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Problem of the Team
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Performance
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Tools for Visual Studio
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Download
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Features
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Demos
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Example Problem
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Traditional GUI
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Rich IDE
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ODBC
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Packages
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Accessing Data
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Remote Execution Context
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Parallelized Algorithms
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Feature Engineering
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Query
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Results
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Histograms
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Correlation Matrix
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Running again
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Linear models
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Scoring
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Graph and Model
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Serialize Models
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Deposit Models
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Stored Procedures
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Prediction Operator
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R Code
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Result
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Screen Resolution
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Summary
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Practicality
Description:
Explore advanced R analytics in SQL Server 2016 using R Tools for Visual Studio in this comprehensive presentation from PASS Data Community Summit. Dive into the world of predictive analytics, understanding its importance across industries and the challenges faced in adoption. Learn a three-step process for implementing predictive analytics and discover how R Tools for Visual Studio can enhance your workflow. Follow along with demos showcasing problem-solving techniques, data access methods, remote execution contexts, and parallelized algorithms. Gain insights into feature engineering, linear modeling, scoring, and model serialization. Understand how to integrate R code with SQL Server through stored procedures and prediction operators. Conclude with practical tips for implementing these advanced analytics techniques in your projects.

Advanced R Analytics in SS2016 Using R Tools for Visual Studio

PASS Data Community Summit
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