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 Title: Data Science: Theories, Models, Algorithms, and Analytics
 Author(s) Sanjiv Ranjan Das
 Publisher: Selfpublishing via GitHub; eBook (Apache Licensed)
 License(s): Apache License, Version 2.0
 Hardcover/Paperback: 288 pages
 eBook: HTML and PDF
 Language: English
 ISBN10/ASIN: N/A
 ISBN13: N/A
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Book Description
The goal of data science is to improve decision making through the analysis of data. Today data science determines the ads we see online, the books and movies that are recommended to us online, which emails are filtered into our spam folders, and even how much we pay for health insurance.
This book provides a bucket full of information regarding Data Science, covers a wide variety of sections by giving access to theories, data science algorithms, tools and analytics. Some highlighting contents of the book are Open Source: Modelling in R to Bayes Theorem.
It offers a concise introduction to the emerging field of data science, explaining its evolution, current uses, data infrastructure issues, and ethical challenges. You'll explore the right approach to data science project management, along with useful tips and best practices to guide you along the way.
 Learn the basics of data science and explore its possibilities and limitations
 Manage data science projects and assemble teams effectively even in the most challenging situations
 Understand management principles and approaches for data science projects to streamline the innovation process
 Data Science
 Data Analysis and Data Mining, Big Data
 The R Programming Language
 Statistics, Mathematical Statistics, and SAS Programming
 Data Science: Theories, Models, Algorithms, and Analytics (Sanjiv Ranjan Das)
 PDF Format (462 pages, 14.3 MB)

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