Articles liés à Hands-On Data Science for Librarians

Hands-On Data Science for Librarians - Couverture souple

Livre 24 sur 36: Chapman & Hall/CRC Data Science

Lin, Sarah; Scott, Dorris

 
9781032080826: Hands-On Data Science for Librarians

Synopsis

Librarians understand the need to store, use and analyze data related to their collection, patrons and institution, and there has been consistent interest over the last 10 years to improve data management, analysis, and visualization skills within the profession. However, librarians find it difficult to move from out-of-the-box proprietary software applications to the skills necessary to perform the range of data science actions in code. This book will focus on teaching R through relevant examples and skills that librarians need in their day-to-day lives that includes visualizations but goes much further to include web scraping, working with maps, creating interactive reports, machine learning, and others. While there’s a place for theory, ethics, and statistical methods, librarians need a tool to help them acquire enough facility with R to utilize data science skills in their daily work, no matter what type of library they work at (academic, public or special). By walking through each skill and its application to library work before walking the reader through each line of code, this book will support librarians who want to apply data science in their daily work. Hands-On Data Science for Librarians is intended for librarians (and other information professionals) in any library type (public, academic or special) as well as graduate students in library and information science (LIS).

Key Features

:

  • Only data science book available geared toward librarians that includes step-by-step code examples
  • Examples include all library types (public, academic, special)
  • Relevant datasets
  • Accessible to non-technical professionals
  • Focused on job skills and their applications

Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.

À propos de l'auteur

Sarah Lin is the Senior Information & Content Architect at MongoDB.

Dorris Scott, PhD is the Academic Director of Data Studies at Washington University in St. Louis.

À propos de la quatrième de couverture

This book will focus on teaching R through relevant examples and skills that librarians need in their day-to-day lives that includes visualizations but goes much further to include web scraping, working with maps, creating interactive reports, machine learning, and others.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.