Introduction to Data Science : Data Analysis and Prediction Algorithms with R

Pages: 713, Specialty: Mathematics, Publisher: Taylor & Francis, Publication Year: 2020, Cover: Hardback, Dimensions: 178x254x40.64mm Introduction to Data Science: Data Analysis and Prediction Algorithms with R 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, data visualization, predictive algorithm building, file organization with UNIX/Linux shell, version control with Git and GitHub, and reproducible document preparation. This book is 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 book is divided into six parts: R, data visualiza