Simply put, data science is the discipline of extracting meaning from data. More and more business analysts are called to work as data scientists and while it can involve deep knowledge of statistics, mathematics, machine learning, and computer science; for most non-academics, data science looks like applying analysis techniques to answer key business questions. Sophisticated s...(展开全部)

Simply put, data science is the discipline of extracting meaning from data. More and more business analysts are called to work as data scientists and while it can involve deep knowledge of statistics, mathematics, machine learning, and computer science; for most non-academics, data science looks like applying analysis techniques to answer key business questions. Sophisticated s...(展开全部)

Practical Data Science with R, Second Edition takes a practice-oriented approach to explaining basic principles in the ever expanding field of data science. You'll jump right to real-world use cases as you apply the R programming language and statistical analysis techniques to carefully explained examples based in marketing, business intelligence, and decision support. Foreword...(展开全部)

Modern Data Science with R is a comprehensive data science textbook for undergraduates that incorporates statistical and computational thinking to solve real-world data problems. Rather than focus exclusively on case studies or programming syntax, this book illustrates how statistical programming in the state-of-the-art R/RStudio computing environment can be leveraged to extrac...(展开全部)

Modern Data Science with R is a comprehensive data science textbook for undergraduates that incorporates statistical and computational thinking to solve real-world data problems. Rather than focus exclusively on case studies or programming syntax, this book illustrates how statistical programming in the state-of-the-art R/RStudio computing environment can be leveraged to extrac...(展开全部)

This book is for users who are familiar with computational methods. If you want to learn about the advanced features of R, including the computer-intense Monte-Carlo methods as well as computational tools for statistical simulation, then this book is for you. Good knowledge of R programming is assumed/required.

This book is for users who are familiar with computational methods. If you want to learn about the advanced features of R, including the computer-intense Monte-Carlo methods as well as computational tools for statistical simulation, then this book is for you. Good knowledge of R programming is assumed/required.

Prabhanjan Tattar has 9 years of experience as a statistical analyst. His main thurst has been to explain statistical and machine learning techniques through elegant programming which will clear the nuances of the underlying mathematics. Survival analysis and statistical inference are his main areas of research/interest, and he has published several research papers in peer-revi...(展开全部)