Regression Analysis with R
Ciaburro, Giuseppe
Sold by GreatBookPricesUK, Woodford Green, United Kingdom
AbeBooks Seller since 28 January 2020
New - Soft cover
Condition: New
Quantity: Over 20 available
Add to basketSold by GreatBookPricesUK, Woodford Green, United Kingdom
AbeBooks Seller since 28 January 2020
Condition: New
Quantity: Over 20 available
Add to basketBuild effective regression models in R to extract valuable insights from real data
Regression analysis is a statistical process which enables prediction of relationships between variables. The predictions are based on the casual effect of one variable upon another. Regression techniques for modeling and analyzing are employed on large set of data in order to reveal hidden relationship among the variables.
This book will give you a rundown explaining what regression analysis is, explaining you the process from scratch. The first few chapters give an understanding of what the different types of learning are - supervised and unsupervised, how these learnings differ from each other. We then move to covering the supervised learning in details covering the various aspects of regression analysis. The outline of chapters are arranged in a way that gives a feel of all the steps covered in a data science process - loading the training dataset, handling missing values, EDA on the dataset, transformations and feature engineering, model building, assessing the model fitting and performance, and finally making predictions on unseen datasets. Each chapter starts with explaining the theoretical concepts and once the reader gets comfortable with the theory, we move to the practical examples to support the understanding. The practical examples are illustrated using R code including the different packages in R such as R Stats, Caret and so on. Each chapter is a mix of theory and practical examples.
By the end of this book you will know all the concepts and pain-points related to regression analysis, and you will be able to implement your learning in your projects.
This book is intended for budding data scientists and data analysts who want to implement regression analysis techniques using R. If you are interested in statistics, data science, machine learning and wants to get an easy introduction to the topic, then this book is what you need! Basic understanding of statistics and math will help you to get the most out of the book. Some programming experience with R will also be helpful
Giuseppe Ciaburro holds a PhD in environmental technical physics and two master's degrees. His research was focused on machine learning applications in the study of the urban sound environments. He works at Built Environment Control Laboratory - Universitą degli Studi della Campania Luigi Vanvitelli (Italy). He has over 15 years of work experience in programming (Python, R, and MATLAB), first in the field of combustion and then in acoustics and noise control. He has several publications to his credit.
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