R: Predictive Analysis

Nonfiction, Computers, Database Management, Application Software
Cover of the book R: Predictive Analysis by Tony Fischetti, Eric Mayor, Rui Miguel Forte, Packt Publishing
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: Tony Fischetti, Eric Mayor, Rui Miguel Forte ISBN: 9781788290852
Publisher: Packt Publishing Publication: March 31, 2017
Imprint: Packt Publishing Language: English
Author: Tony Fischetti, Eric Mayor, Rui Miguel Forte
ISBN: 9781788290852
Publisher: Packt Publishing
Publication: March 31, 2017
Imprint: Packt Publishing
Language: English

Master the art of predictive modeling

About This Book

  • Load, wrangle, and analyze your data using the world's most powerful statistical programming language
  • Familiarize yourself with the most common data mining tools of R, such as k-means, hierarchical regression, linear regression, Naive Bayes, decision trees, text mining and so on.
  • We emphasize important concepts, such as the bias-variance trade-off and over-fitting, which are pervasive in predictive modeling

Who This Book Is For

If you work with data and want to become an expert in predictive analysis and modeling, then this Learning Path will serve you well. It is intended for budding and seasoned practitioners of predictive modeling alike. You should have basic knowledge of the use of R, although it's not necessary to put this Learning Path to great use.

What You Will Learn

  • Get to know the basics of R's syntax and major data structures
  • Write functions, load data, and install packages
  • Use different data sources in R and know how to interface with databases, and request and load JSON and XML
  • Identify the challenges and apply your knowledge about data analysis in R to imperfect real-world data
  • Predict the future with reasonably simple algorithms
  • Understand key data visualization and predictive analytic skills using R
  • Understand the language of models and the predictive modeling process

In Detail

Predictive analytics is a field that uses data to build models that predict a future outcome of interest. It can be applied to a range of business strategies and has been a key player in search advertising and recommendation engines.

The power and domain-specificity of R allows the user to express complex analytics easily, quickly, and succinctly. R offers a free and open source environment that is perfect for both learning and deploying predictive modeling solutions in the real world. This Learning Path will provide you with all the steps you need to master the art of predictive modeling with R.

We start with an introduction to data analysis with R, and then gradually you'll get your feet wet with predictive modeling. You will get to grips with the fundamentals of applied statistics and build on this knowledge to perform sophisticated and powerful analytics. You will be able to solve the difficulties relating to performing data analysis in practice and find solutions to working with “messy data”, large data, communicating results, and facilitating reproducibility. You will then perform key predictive analytics tasks using R, such as train and test predictive models for classification and regression tasks, score new data sets and so on. By the end of this Learning Path, 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.

This Learning Path combines some of the best that Packt has to offer in one complete, curated package. It includes content from the following Packt products:

  • Data Analysis with R, Tony Fischetti
  • Learning Predictive Analytics with R, Eric Mayor
  • Mastering Predictive Analytics with R, Rui Miguel Forte

Style and approach

Learn data analysis using engaging examples and fun exercises, and with a gentle and friendly but comprehensive "learn-by-doing" approach. This is a practical course, which analyzes compelling data about life, health, and death with the help of tutorials. It offers you a useful way of interpreting the data that's specific to this course, but that can also be applied to any other data. This course is designed to be both a guide and a reference for moving beyond the basics of predictive modeling.

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

Master the art of predictive modeling

About This Book

Who This Book Is For

If you work with data and want to become an expert in predictive analysis and modeling, then this Learning Path will serve you well. It is intended for budding and seasoned practitioners of predictive modeling alike. You should have basic knowledge of the use of R, although it's not necessary to put this Learning Path to great use.

What You Will Learn

In Detail

Predictive analytics is a field that uses data to build models that predict a future outcome of interest. It can be applied to a range of business strategies and has been a key player in search advertising and recommendation engines.

The power and domain-specificity of R allows the user to express complex analytics easily, quickly, and succinctly. R offers a free and open source environment that is perfect for both learning and deploying predictive modeling solutions in the real world. This Learning Path will provide you with all the steps you need to master the art of predictive modeling with R.

We start with an introduction to data analysis with R, and then gradually you'll get your feet wet with predictive modeling. You will get to grips with the fundamentals of applied statistics and build on this knowledge to perform sophisticated and powerful analytics. You will be able to solve the difficulties relating to performing data analysis in practice and find solutions to working with “messy data”, large data, communicating results, and facilitating reproducibility. You will then perform key predictive analytics tasks using R, such as train and test predictive models for classification and regression tasks, score new data sets and so on. By the end of this Learning Path, 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.

This Learning Path combines some of the best that Packt has to offer in one complete, curated package. It includes content from the following Packt products:

Style and approach

Learn data analysis using engaging examples and fun exercises, and with a gentle and friendly but comprehensive "learn-by-doing" approach. This is a practical course, which analyzes compelling data about life, health, and death with the help of tutorials. It offers you a useful way of interpreting the data that's specific to this course, but that can also be applied to any other data. This course is designed to be both a guide and a reference for moving beyond the basics of predictive modeling.

More books from Packt Publishing

Cover of the book Building a Home Security System with BeagleBone by Tony Fischetti, Eric Mayor, Rui Miguel Forte
Cover of the book Learn to Create WordPress Themes by Building 5 Projects. by Tony Fischetti, Eric Mayor, Rui Miguel Forte
Cover of the book Implementing Samba 4 by Tony Fischetti, Eric Mayor, Rui Miguel Forte
Cover of the book Getting Started with Tableau 2018.x by Tony Fischetti, Eric Mayor, Rui Miguel Forte
Cover of the book Learning ClojureScript by Tony Fischetti, Eric Mayor, Rui Miguel Forte
Cover of the book Joomla! Web Security by Tony Fischetti, Eric Mayor, Rui Miguel Forte
Cover of the book Practical Game AI Programming by Tony Fischetti, Eric Mayor, Rui Miguel Forte
Cover of the book Building Mapping Applications with QGIS by Tony Fischetti, Eric Mayor, Rui Miguel Forte
Cover of the book PHP jQuery Cookbook by Tony Fischetti, Eric Mayor, Rui Miguel Forte
Cover of the book OpenJDK Cookbook by Tony Fischetti, Eric Mayor, Rui Miguel Forte
Cover of the book Cracking the IT Architect Interview by Tony Fischetti, Eric Mayor, Rui Miguel Forte
Cover of the book Mastering F# by Tony Fischetti, Eric Mayor, Rui Miguel Forte
Cover of the book Kali Linux Cookbook - Second Edition by Tony Fischetti, Eric Mayor, Rui Miguel Forte
Cover of the book Big Data Analytics by Tony Fischetti, Eric Mayor, Rui Miguel Forte
Cover of the book Developing Microsoft Dynamics GP Business Applications by Tony Fischetti, Eric Mayor, Rui Miguel Forte
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy