Mastering Predictive Analytics with R

by Rui Miguel Forte

Master the craft of predictive modeling by developing strategy, intuition, and a solid foundation in essential conceptsAbout This BookGrasp the major methods of predictive modeling and move beyond black box thinking to a deeper level of understandingLeverage the flexibility and modularity of R to experiment with a range of different techniques and data typesPacked with practical advice and tips explaining important concepts and best practices to help you understand quickly and easilyWho This Book Is ForThis book is intended for the budding data scientist, predictive modeler, or quantitative analyst with only a basic exposure to R and statistics. It is also designed to be a reference for experienced professionals wanting to brush up on the details of a particular type of predictive model. Mastering Predictive Analytics with R assumes familiarity with only the fundamentals of R, such as the main data types, simple functions, and how to move data around. No prior experience with machine learning or predictive modeling is assumed, however you should have a basic understanding of statistics and calculus at a high school level.

What You Will LearnMaster the steps involved in the predictive modeling processLearn how to classify predictive models and distinguish which models are suitable for a particular problemUnderstand how and why each predictive model worksRecognize the assumptions, strengths, and weaknesses of a predictive model, and that there is no best model for every problemSelect appropriate metrics to assess the performance of different types of predictive modelDiagnose performance and accuracy problems when they arise and learn how to deal with themGrow your expertise in using R and its diverse range of packagesIn DetailR 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.

416 pages, Kindle Edition

First published June 17, 2015

Reviews

[Yahia El gamal · Rating 4 out of 5]

Amazing book. Goes through a lot of very relevant algorithms and describes the intuition of it. It coasts at a very good level between explaining enough so the understanding is complete, while giving hints on where you can delve deeper.

I especially recommend it for people who need good refreshing of what they studied before. Especially for interviews!