Parallel Computing for Data Science

Focusing on parallel data structures and algorithms, this book serves as a comprehensive guide for those interested in parallel computing within data science. It equips readers with the skills to write effective parallel code across multiple programming languages and explores various R packages and tools. The content includes discussions on the classic "n observations, p variables" matrix format, alongside common data structures, complemented by numerous examples that highlight the challenges faced in parallel programming.