24,95 €
24,95 €
inkl. MwSt.
Sofort per Download lieferbar
payback
12 °P sammeln
24,95 €
24,95 €
inkl. MwSt.
Sofort per Download lieferbar

Alle Infos zum eBook verschenken
payback
12 °P sammeln
Als Download kaufen
24,95 €
inkl. MwSt.
Sofort per Download lieferbar
payback
12 °P sammeln
Jetzt verschenken
24,95 €
inkl. MwSt.
Sofort per Download lieferbar

Alle Infos zum eBook verschenken
payback
12 °P sammeln
  • Format: PDF

Python for Information Professionals: How to Design Practical Applications to Capitalize on the Data Explosion is an introduction to the Python programming language for library and information professionals with little or no prior experience. As opposed to the many Python books available today that focus on the language only from a general sense, this book is designed specifically for information professionals who are seeking to advance their career prospects or challenge themselves in new ways by acquiring skills within the rapidly expanding field of data science. Readers of Python for…mehr

Produktbeschreibung
Python for Information Professionals: How to Design Practical Applications to Capitalize on the Data Explosion is an introduction to the Python programming language for library and information professionals with little or no prior experience. As opposed to the many Python books available today that focus on the language only from a general sense, this book is designed specifically for information professionals who are seeking to advance their career prospects or challenge themselves in new ways by acquiring skills within the rapidly expanding field of data science. Readers of Python for Information Professionals will learn to: Develop Python applications for the retrieval, cleaning, and analysis of large datasets. Design applications to support traditional library functions and create new opportunities to maximize library value. Consider data security and privacy relevant to data analysis when using the Python language.
Autorenporträt
Brady Lund, Ph.D., is an assistant professor of information science at the University of North Texas. He has published four books related to technology in libraries and educational institutions - including Casting Light on the Dark Web and Creating Accessible Online Instruction Using Universal Design Principles, both for Rowman and Littlefield Publishing - and nearly 100 articles, editorials, and opinion papers. His work often combines data analytics principles with library and information science research topics. Daniel Agbaji is a Ph.D. student in information science at the University of North Texas, with a major in Data Science-Artificial Intelligence and Machine Learning. As an experienced researcher and software developer, he has written scholarly publications and book chapters with notable publishers. Daniel has published articles in the information science and library field. As a software developer, Daniel has written thousands of lines of code for fortune 500 companies which are not publicly available due to company policies.