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.
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.
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.
Inhaltsangabe
Preface Part I: Python: The Basics Chapter 1 - The Python WorkspaceChapter 2 - Object Oriented ProgrammingChapter 3 - Data Types, Structures, Sets and AlgorithmsChapter 4 - Functions: Code that Puts Our Data to WorkChapter 5 - Importing, Creating, and Maintaining Data FilesChapter 6 - Testing and TroubleshootingPart II: Further Applications of Python in Information Organizations Chapter 7 - Library Management and Usage DataChapter 8 - Library Research Data ManagementChapter 9 - Text AnalysisChapter 10 - Library and Information Science ResearchChapter 11 - Artificial Intelligence ApplicationsPart III: Practical and Ethical Considerations for Using Python Chapter 12 - Data Explosion, Big Data, and Data LiteracyChapter 13 - Data EthicsChapter 14 - Knowledge and Data EconomyChapter 15 - Further Resources for Advancing Your Python Mastery Glossary Index About the Author
Preface Part I: Python: The Basics Chapter 1 - The Python WorkspaceChapter 2 - Object Oriented ProgrammingChapter 3 - Data Types, Structures, Sets and AlgorithmsChapter 4 - Functions: Code that Puts Our Data to WorkChapter 5 - Importing, Creating, and Maintaining Data FilesChapter 6 - Testing and TroubleshootingPart II: Further Applications of Python in Information Organizations Chapter 7 - Library Management and Usage DataChapter 8 - Library Research Data ManagementChapter 9 - Text AnalysisChapter 10 - Library and Information Science ResearchChapter 11 - Artificial Intelligence ApplicationsPart III: Practical and Ethical Considerations for Using Python Chapter 12 - Data Explosion, Big Data, and Data LiteracyChapter 13 - Data EthicsChapter 14 - Knowledge and Data EconomyChapter 15 - Further Resources for Advancing Your Python Mastery Glossary Index About the Author
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