Sunday, October 30, 2016

Online Data Analytics with R: A hands-on approach by Viswa Viswanathan eBook or Kindle ePUB free

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Data Analytics with R: A hands-on approach Even more crucially, we also have easy access -- through our personal computers and powerful free software packages -- to the means to process the corpus of data and extract intelligence from it. Qui
Dr. Viswa Viswanathan teaches Computing and Decision Sciences at Seton Hall University in New Jersey, USA. In addition to his significant teaching experience at the Indian Institute of Management, Kolkata and at Seton Hall University, he has spent a decade in the software industry in the US and in India. He enjoys developing and deploying significant web-applications. Viswa has authored several peer-reviewed scholarly articles in leading journals like Operations Research, IEEE Software, International Journal of Artificial Intelligence in Education and Computers and Industrial Engineering. His work has touched many fields including information systems, artificial intelligence, Operations Research, software development and computer based learning. Viswa's keen interest in understanding how people learn and his evidence-based conviction that people learn best by doing has led him to explore new approaches to helping people to learn advanced concepts. Through his writing, he hopes to make


 

Title:Data Analytics with R: A hands-on approach
Author:Viswa Viswanathan
Format:Paperback - Pages ( 364 )
Rating:4.58
Publish Date:2014-05-30
Id Book:1941773001
Type File:PDF, DOC, RTF, ePub

Today we all have access to a lot of data. Even more crucially, we also have easy access -- through our personal computers and powerful free software packages -- to the means to process the corpus of data and extract intelligence from it. Quite needlessly though, the necessary knowledge skills remain the exclusive preserve of a few, which this book sets out to change. Although most data analytics techniques have a mathematical basis, people with a grasp of high school mathematics can gain a deep intuitive understanding of the underlying techniques and apply them correctly and effectively. To make this possible, the book:

  • Focuses on intuitive and correct explanations with examples, while avoiding deep mathematics;
  • Provides numerous examples, tables and figures (almost 170 figures and 105 tables), to help readers grasp the concepts and techniques;
  • Introduces the R statistical programming environment and provides step-by-step guidance to learn R and apply it to t


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