Practical Data Science for Information Professionals
eBook - PDF

Practical Data Science for Information Professionals

  1. 208 pages
  2. English
  3. PDF
  4. Available on iOS & Android
eBook - PDF

Practical Data Science for Information Professionals

About this book

Practical Data Science for Information Professionals provides an accessible introduction to a potentially complex field, providing readers with an overview of data science and a framework for its application. It provides detailed examples and analysis on real data sets to explore the basics of the subject in three principle areas: clustering and social network analysis; predictions and forecasts; and text analysis and mining.

As well as highlighting a wealth of user-friendly data science tools, the book also includes some example code in two of the most popular programming languages ( R and Python ) to demonstrate the ease with which the information professional can move beyond the graphical user interface and achieve significant analysis with just a few lines of code.

After reading, readers will understand:

· the growing importance of data science

· the role of the information professional in data science

· some of the most important tools and methods that information professionals can use.

Bringing together the growing importance of data science and the increasing role of information professionals in the management and use of data, Practical Data Science for Information Professionals will provide a practical introduction to the topic specifically designed for the information community. It will appeal to librarians and information professionals all around the world, from large academic libraries to small research libraries. By focusing on the application of open source software, it aims to reduce barriers for readers to use the lessons learned within.

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Yes, you can access Practical Data Science for Information Professionals by David Stuart in PDF and/or ePUB format, as well as other popular books in Languages & Linguistics & Library & Information Science. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Title page
  2. Contents
  3. 1 What is data science?
  4. 2 Little data, big data
  5. 3 The process of data science
  6. 4 Tools for data analysis
  7. 5 Clustering and social network analysis
  8. 6 Predictions and forecasts
  9. 7 Text analysis and mining
  10. 8 The future of data science and information professionals
  11. References
  12. Appendix – Programming concepts for data science
  13. Index