Learning Predictive Analytics with R: Get to grips with key data visualization and predictive analytic skills using R

Eric Mayor

$54.99

3 (2 Ratings)

Paperback Sep 2015 332 pages 1st Edition

Eric Mayor

$54.99

3 (2 Ratings)

Paperback Sep 2015 332 pages 1st Edition

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Key benefits

Acquire predictive analytic skills using various tools of R
Make predictions about future events by discovering valuable information from data using R
Comprehensible guidelines that focus on predictive model design with real-world data

Description

This book is packed with easy-to-follow guidelines that explain the workings of the many key data mining tools of R, which are used to discover knowledge from your data. You will learn how to 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. All chapters will guide you in acquiring the skills in a practical way. Most chapters also include a theoretical introduction that will sharpen your understanding of the subject matter and invite you to go further. The book familiarizes you with the most common data mining tools of R, such as k-means, hierarchical regression, linear regression, association rules, principal component analysis, multilevel modeling, k-NN, Naïve Bayes, decision trees, and text mining. It also provides a description of visualization techniques using the basic visualization tools of R as well as lattice for visualizing patterns in data organized in groups. This book is invaluable for anyone fascinated by the data mining opportunities offered by GNU R and its packages.

Who is this book for?

If you are a statistician, chief information officer, data scientist, ML engineer, ML practitioner, quantitative analyst, and student of machine learning, this is the book for you. You should have basic knowledge of the use of R. Readers without previous experience of programming in R will also be able to use the tools in the book.

What you will learn

Customize R by installing and loading new packages
Explore the structure of data using clustering algorithms
Turn unstructured text into ordered data, and acquire knowledge from the data
Classify your observations using Naïve Bayes, k-NN, and decision trees
Reduce the dimensionality of your data using principal component analysis
Discover association rules using Apriori
Understand how statistical distributions can help retrieve information from data using correlations, linear regression, and multilevel regression
Use PMML to deploy the models generated in R

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r pike Jul 18, 2016

I enjoyed reading this. As a beginner in predictive analytics, for me, it was informative. The subject matter is vast and no one book would be able to get someone started in the field of study but this was a good start for me.

Amazon Verified review

Dimitri Shvorob Mar 03, 2016

Packt's conveyor is not slowing down: only three months ago I surveyed their fresh crop of "data science with R" offerings"Mastering Predictive Analytics with R" by Forte, £32.99"Mastering Machine Learning with R" by Lesmeister, £34.99"R Data Analysis Cookbook" by Viswanathan and Viswanathan, £29.99"Machine Learning with R Cookbook" by Yu-Wei, £30.99and now there are four more:"Unsupervised Learning with R" by Pacheco, £25.99"Data Analysis with R" by Fischetti, £34.99"Learning Predictive Analytics with R" by Mayor, £31.99"Mastering Data Analysis with R" by Daroczi, £34.99I have not yet seen Daroszi's book, but Fischetti's book gets my "thumbs up", Pacheco's is an easy "thumbs down", and Mayor's is ... right there with Pacheco's. The book really feels behind the times - cf. use of "lattice" over "ggplot2", and of R Commander instead of RStudio - and the writing is seriously subpar. Contentwise, it's all familiar stuff - even the dreadful book by Lesmeister could manage "caret" usage examples - and coverage is actually on the narrow side. What could *possibly* be the book's "unique selling proposition"?Kabacoff, Forte, Lantz, Cotton, Kuhn - check out the books by any of these authors, and erase this one from your memory.UPD. With the benefit of a little more life experience, I would say: don't spend your time on *any* R book. Python is the way to go.

Learning Predictive Analytics with R: Get to grips with key data visualization and predictive analytic skills using R

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