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Book DescriptionThis 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 learn Master the steps involved in the predictive modeling process Learn how to classify predictive models and distinguish which models are suitable for a particular problem Understand how and why each predictive model works Recognize the assumptions, strengths, and weaknesses of a predictive model, and that there is no best model for every problem Select appropriate metrics to assess the performance of different types of predictive model Diagnose performance and accuracy problems when they arise and learn how to deal with them Grow your expertise in using R and its diverse range of packages Who 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.