Practical Data Science for Information Professionals
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 s...
Uloženo v:
| Hlavní autor: | |
|---|---|
| Médium: | E-kniha |
| Jazyk: | angličtina |
| Vydáno: |
London
Facet Publishing
2020
Facet |
| Vydání: | 1 |
| Témata: | |
| ISBN: | 1783303468, 9781783303465, 178330345X, 9781783303458 |
| On-line přístup: | Získat plný text |
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Obsah:
- Intro -- Title page -- Contents -- Preface -- 1 What is data science? -- Data, information, knowledge, wisdom -- Data everywhere -- The data deserts -- Data science -- The potential of data science -- From research data services to data science in libraries -- Programming in libraries -- Programming in this book -- The structure of this book -- 2 Little data, big data -- Big data -- Data formats -- Standalone files -- Application programming interfaces -- Unstructured data -- Data sources -- Data licences -- 3 The process of data science -- Modelling the data science process -- Frame the problem -- Collect data -- Transform and clean data -- Analyse data -- Visualise and communicate data -- Frame a new problem -- 4 Tools for data analysis -- Finding tools -- Software for data science -- Programming for data science -- 5 Clustering and social network analysis -- Network graphs -- Graph terminology -- Network matrix -- Visualisation -- Network analysis -- 6 Predictions and forecasts -- Predictions and forecasts beyond data science -- Predictions in a world of (limited) data -- Predicting and forecasting for information professionals -- Statistical methodologies -- 7 Text analysis and mining -- Text analysis and mining, and information professionals -- Natural language processing -- Keywords and n-grams -- 8 The future of data science and information professionals -- Eight challenges to data science -- Ten steps to data science librarianship -- The final word: play -- References -- Appendix - Programming concepts for data science -- Variables, data types and other classes -- Import libraries -- Functions and methods -- Loops and conditionals -- Final words of advice -- Further reading -- Index