Mastering Predictive Analytics with R

Nonfiction, Computers, Advanced Computing, Programming, Data Modeling & Design, Database Management
Cover of the book Mastering Predictive Analytics with R by Rui Miguel Forte, Packt Publishing
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Author: Rui Miguel Forte ISBN: 9781783982813
Publisher: Packt Publishing Publication: June 17, 2015
Imprint: Packt Publishing Language: English
Author: Rui Miguel Forte
ISBN: 9781783982813
Publisher: Packt Publishing
Publication: June 17, 2015
Imprint: Packt Publishing
Language: English

R offers a free and open source environment that is perfect for both learning and deploying predictive modeling solutions in the real world. With its constantly growing community and plethora of packages, R offers the functionality to deal with a truly vast array of problems.

This book is designed to be both a guide and a reference for moving beyond the basics of predictive modeling. The book begins with a dedicated chapter on the language of models and the predictive modeling process. Each subsequent chapter tackles a particular type of model, such as neural networks, and focuses on the three important questions of how the model works, how to use R to train it, and how to measure and assess its performance using real world data sets.

By the end of this book, you will have explored and tested the most popular modeling techniques in use on real world data sets and mastered a diverse range of techniques in predictive analytics.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

R offers a free and open source environment that is perfect for both learning and deploying predictive modeling solutions in the real world. With its constantly growing community and plethora of packages, R offers the functionality to deal with a truly vast array of problems.

This book is designed to be both a guide and a reference for moving beyond the basics of predictive modeling. The book begins with a dedicated chapter on the language of models and the predictive modeling process. Each subsequent chapter tackles a particular type of model, such as neural networks, and focuses on the three important questions of how the model works, how to use R to train it, and how to measure and assess its performance using real world data sets.

By the end of this book, you will have explored and tested the most popular modeling techniques in use on real world data sets and mastered a diverse range of techniques in predictive analytics.

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