Brady Lund, Daniel Agbaji, Kossi Dodzi Bissadu
Python for Information Professionals
How to Design Practical Applications to Capitalize on the Data Explosion
Brady Lund, Daniel Agbaji, Kossi Dodzi Bissadu
Python for Information Professionals
How to Design Practical Applications to Capitalize on the Data Explosion
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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.
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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.
Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Produktdetails
- Produktdetails
- Verlag: Rowman & Littlefield
- Seitenzahl: 172
- Erscheinungstermin: 1. November 2023
- Englisch
- Abmessung: 235mm x 157mm x 14mm
- Gewicht: 404g
- ISBN-13: 9781538178249
- ISBN-10: 1538178249
- Artikelnr.: 68284016
- Verlag: Rowman & Littlefield
- Seitenzahl: 172
- Erscheinungstermin: 1. November 2023
- Englisch
- Abmessung: 235mm x 157mm x 14mm
- Gewicht: 404g
- ISBN-13: 9781538178249
- ISBN-10: 1538178249
- Artikelnr.: 68284016
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. Kossi Dodzi Bissadu is a Ph.D. student in the computer science at the University of North Texas. He currently works as a software engineer at Zenner USA where he leads various products, software, applications, and systems development projects. He is also a US Air Force veteran, very talented and dedicated professional who has more than ten-year professional record achievements, and demonstrated success leading, managing, and working in Technology and Sciences. Kossi has several industry certifications including certified blockchain developer, AWS certified cloud practitioner, and CompTIA Security+. Haihua Chen, Ph.D., is a clinical assistant professor of information science at the University of North Texas. He has more than ten years of experience in Python and five years of experience in teaching technical courses for information science and data science students using Python. Dr. Chen has published nearly 40 articles on natural language processing, machine learning, data quality, information retrieval, digital libraries, and applied data science. He is the editor of The Electronic Library and the leading guest editor of Frontiers in Big Data and Information Discovery & Delivery special issues. He is also serving as the reviewer/ PC member for more than 20 peer-review journals/ conferences in information science and computer science.
Preface
Part I: Python: The Basics
* Chapter 1 - The Python Workspace
* Chapter 2 - Object Oriented Programming
* Chapter 3 - Data Types, Structures, Sets and Algorithms
* Chapter 4 - Functions: Code that Puts Our Data to Work
* Chapter 5 - Importing, Creating, and Maintaining Data Files
* Chapter 6 - Testing and Troubleshooting
Part II: Further Applications of Python in Information Organizations
* Chapter 7 - Library Management and Usage Data
* Chapter 8 - Library Research Data Management
* Chapter 9 - Text Analysis
* Chapter 10 - Library and Information Science Research
* Chapter 11 - Artificial Intelligence Applications
Part III: Practical and Ethical Considerations for Using Python
* Chapter 12 - Data Explosion, Big Data, and Data Literacy
* Chapter 13 - Data Ethics
* Chapter 14 - Knowledge and Data Economy
* Chapter 15 - Further Resources for Advancing Your Python Mastery
Glossary
Index
About the Author
Part I: Python: The Basics
* Chapter 1 - The Python Workspace
* Chapter 2 - Object Oriented Programming
* Chapter 3 - Data Types, Structures, Sets and Algorithms
* Chapter 4 - Functions: Code that Puts Our Data to Work
* Chapter 5 - Importing, Creating, and Maintaining Data Files
* Chapter 6 - Testing and Troubleshooting
Part II: Further Applications of Python in Information Organizations
* Chapter 7 - Library Management and Usage Data
* Chapter 8 - Library Research Data Management
* Chapter 9 - Text Analysis
* Chapter 10 - Library and Information Science Research
* Chapter 11 - Artificial Intelligence Applications
Part III: Practical and Ethical Considerations for Using Python
* Chapter 12 - Data Explosion, Big Data, and Data Literacy
* Chapter 13 - Data Ethics
* Chapter 14 - Knowledge and Data Economy
* Chapter 15 - Further Resources for Advancing Your Python Mastery
Glossary
Index
About the Author
Preface
Part I: Python: The Basics
* Chapter 1 - The Python Workspace
* Chapter 2 - Object Oriented Programming
* Chapter 3 - Data Types, Structures, Sets and Algorithms
* Chapter 4 - Functions: Code that Puts Our Data to Work
* Chapter 5 - Importing, Creating, and Maintaining Data Files
* Chapter 6 - Testing and Troubleshooting
Part II: Further Applications of Python in Information Organizations
* Chapter 7 - Library Management and Usage Data
* Chapter 8 - Library Research Data Management
* Chapter 9 - Text Analysis
* Chapter 10 - Library and Information Science Research
* Chapter 11 - Artificial Intelligence Applications
Part III: Practical and Ethical Considerations for Using Python
* Chapter 12 - Data Explosion, Big Data, and Data Literacy
* Chapter 13 - Data Ethics
* Chapter 14 - Knowledge and Data Economy
* Chapter 15 - Further Resources for Advancing Your Python Mastery
Glossary
Index
About the Author
Part I: Python: The Basics
* Chapter 1 - The Python Workspace
* Chapter 2 - Object Oriented Programming
* Chapter 3 - Data Types, Structures, Sets and Algorithms
* Chapter 4 - Functions: Code that Puts Our Data to Work
* Chapter 5 - Importing, Creating, and Maintaining Data Files
* Chapter 6 - Testing and Troubleshooting
Part II: Further Applications of Python in Information Organizations
* Chapter 7 - Library Management and Usage Data
* Chapter 8 - Library Research Data Management
* Chapter 9 - Text Analysis
* Chapter 10 - Library and Information Science Research
* Chapter 11 - Artificial Intelligence Applications
Part III: Practical and Ethical Considerations for Using Python
* Chapter 12 - Data Explosion, Big Data, and Data Literacy
* Chapter 13 - Data Ethics
* Chapter 14 - Knowledge and Data Economy
* Chapter 15 - Further Resources for Advancing Your Python Mastery
Glossary
Index
About the Author