Key FeaturesBook 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 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 packagesWho 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.
