bMaster the craft of predictive modeling in R by developing strategy, intuition, and a solid foundation in essential concepts/bh2About This Book/h2ulliGrasping the major methods of predictive modeling and moving beyond black box thinking to a deeper level of understanding/liliLeveraging the flexibil...

Ausführliche Beschreibung

Bibliographische Detailangaben

1. Verfasser:	Miller, James D. (VerfasserIn)
Format:	Elektronisch E-Book
Sprache:	English
Veröffentlicht:	Birmingham Packt Publishing Limited 2017
Ausgabe:	2
Schlagworte:	COMPUTERS / Data Modeling &amp Design COMPUTERS / Data Visualization
Zusammenfassung:	bMaster the craft of predictive modeling in R by developing strategy, intuition, and a solid foundation in essential concepts/bh2About This Book/h2ulliGrasping the major methods of predictive modeling and moving beyond black box thinking to a deeper level of understanding/liliLeveraging the flexibility and modularity of R to experiment with a range of different techniques and data types/liliPacked with practical advice and tips explaining important concepts and best practices to help you understand quickly and easily/li/ulh2Who This Book Is For/h2Although budding data scientists, predictive modelers, or quantitative analysts with only basic exposure to R and statistics will find this book to be useful, the experienced data scientist professional wishing to attain master level status , will also find this book extremely valuable.. This book assumes familiarity with the fundamentals of R, such as the main data types, simple functions, and how to move data around. Although no prior experience with machine learning or predictive modeling is required, there are some advanced topics provided that will require more than novice exposure.h2What You Will Learn/h2ulliMaster the steps involved in the predictive modeling process/liliGrow your expertise in using R and its diverse range of packages/liliLearn how to classify predictive models and distinguish which models are suitable for a particular problem/liliUnderstand steps for tidying data and improving the performing metrics/liliRecognize the assumptions, strengths, and weaknesses of a predictive model/liliUnderstand how and why each predictive model works in R/liliSelect appropriate metrics to assess the performance of different types of predictive model/liliExplore word embedding and recurrent neural networks in R/liliTrain models in R that can work on very large datasets/li/ulh2In Detail/h2R offers a free and open source environment that is perfect for both learning and deploying predictive modeling solutions. With its constantly growing community and plethora of packages, R offers the functionality to deal with a truly vast array of problems.The book begins with a dedicated chapter on the language of models and the predictive modeling process. You will understand the learning curve and the process of tidying data.
Beschreibung:	1 Online-Ressource (448 Seiten)
ISBN:	9781787124356