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The R Statistical Software is used to provide a comprehensive treatment of statistical inference methods in data science in this book. It offers a crucial, simple-to-understand introduction to statistics and the R programming language.
In only one training course, it is difficult to master R. However, this course seeks to provide a broad overview of many R-related topics.
The exercises from Hadley Wickham's book Advanced R are solved in this book (Edition 2). It is a work in progress that is actively being developed. We hope to include most of the solutions in the second printing of...
This book aids in your fundamental comprehension of R's operation. It is intended for both R programmers who want to learn the language more thoroughly and programmers with experience in other languages who want to learn what makes R...
This book's goal is to introduce readers to R's capabilities for handling and analyzing data. It is designed for people with little to no prior R experience.
This book provides a basic introduction to financial mathematics, emphasizing conceptual model knowledge and problem-solving.
The amount of unstructured and text-heavy data available today makes it difficult for analysts to use their typical data wrangling and visualization techniques.
The purpose of this cookbook is to offer solutions to typical tasks and issues in data analysis. Each recipe contains a discussion of how and why the recipe works as well as a solution you may use in your...
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This book is for you if you wish to understand data science and numerical programming principles through practical, real-world project examples and you are an aspiring data scientist.
With the most recent R code, this book will teach you sophisticated machine-learning techniques. You will study supervised learning and statistical learning theory, create effective algorithms, discover how to make recommendation engines, apply multi-class classification, and more. ...