Introduction to Data Science: Data Analysis and Prediction Algorithms with RКНИГИ » ПРОГРАММИНГ
Название: Introduction to Data Science: Data Analysis and Prediction Algorithms with R Автор: Rafael A. Irizarry Издательство: Independently published Год: 2019 Страниц: 708 Язык: английский Формат: pdf (true) Размер: 68.8 MB
The demand for skilled data science practitioners in industry, academia and government is rapidly growing. This book introduces concepts and skills that can help you tackle real-world data analysis challenges. It covers concepts from probability, statistical inference, linear regression and machine learning. It also helps you develop skills such as R programming, data wrangling with dplyr, data visualization with ggplot2, algorithm building with caret, file organization with UNIX/Linux shell, version control with Git and GitHub, and reproducible document preparation with knitr and R markdown. The book is divided into six parts: R, Data Visualization, Data Wrangling, Probability, Inference and Regression with R, Machine Learning, and Productivity Tools. Each part has several chapters meant to be presented as one lecture. The book includes dozens of exercises distributed across most chapters.
Who will find this book useful? This book is meant to be a textbook for a first course in Data Science. No previous knowledge of R is necessary, although some experience with programming may be helpful. The statistical concepts used to answer the case study questions are only briefly introduced, so a Probability and Statistics textbook is highly recommended for in-depth understanding of these concepts. If you read and understand all the chapters and complete all the exercises, you will be well-positioned to perform basic data analysis tasks and you will be prepared to learn the more advanced concepts and skills needed to become an expert.
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Introduction to Data Science: Data Analysis and Prediction Algorithms with R 
