Data mining -- PeriodicalsSee also what's at your library, or elsewhere.
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Filed under: Data mining -- Periodicals
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Filed under: Data mining- Machine Learning for Data Streams, With Practical Examples in MOA (Cambridge, MA and London: MIT Press, c2017), by Albert Bifet, Ricard Gavaldà, Geoffrey Holmes, and Bernhard Pfahringer (HTML with commentary in New Zealand)
- Mining of Massive Datasets (version 2.1, c2014), by Jurij Leskovec, Anand Rajaraman, and Jeffrey D. Ullman (PDF files with commentary at mmds.org)
- Social Media Mining: An Introduction (prepublication draft, with supplementary materials; 2014), by Reza Zafarani, Mohammad Ali Abbasi, and Huan Liu (PDF with commentary at asu.edu)
- Introduction to Data Science (version 3; c2013), by Jeffrey M. Stanton, contrib. by Robert W. De Graaf (PDF with commentary at Syracuse)
- Bisociative Knowledge Discovery: An Introduction to Concept, Algorithms, Tools, and Applications (c2012), ed. by Michael R. Berthold (PDF files with commentary at SpringerLink)
- Text Mining with R: A Tidy Approach (Creative Commons online edition; ca. 2019), by Julia Silge and David Robinson (illustrated HTML with commentary at tidytextmining.com)
- Python Data Science Handbook (c2016), by Jacob T. Vanderplas (illustrated HTML at Github and jupyter.org)
- A Whirlwind Tour of Python (Sebastopol, CA et al.: O'Reilly Media, c2016), by Jacob T. Vanderplas (PDF at oreilly.com)
- The Data Journalism Handbook (electronic first edition, c2012), ed. by Liliana Bounegru, Lucy Chambers, and Jonathan Gray (illustrated HTML with commentary at datajournalismhandbook.org)
- The Data Journalism Handbook 2: Towards a Critical Data Practice (online edition, ca. 2021), ed. by Jonathan Gray and Liliana Bounegru (illustrated HTML with commentary at datajournalism.com)
- Introduction to Data Science: Data Analysis and Prediction Algorithms With R (Creative Commons online edition, 2021), by Rafael A. Irizarry (illustrated HTML with commentary at github.uio)
- Mining Social Media: Finding Stories in Internet Data (2019), by Lam Thuy Vo (HTML with commentary at socialdata.site)
- The Elements of Statistical Learning: Data Mining, Inference, and Prediction (second edition, 2009), by Trevor Hastie, Robert Tibshirani, and J. H. Friedman (PDF with commentary at Stanford)
- digitalSTS: A Field Guide for Science and Technology Studies (Princeton: Princeton University Press, c2019), ed. by Janet Vertesi and David Ribes (PDF files and multimedia with commentary at digitalsts.net)
- Cloudera Impala (Sebastopol, CA et al: O'Reilly, c2014), by John Russell (page images at cloudera.com)
- Data mining and data warehousing (Association of Research Libraries, Office of Leadership and Management Services, 2003), by Barbara Mento, Brendan Rapple, and Association of Research Libraries. Office of Leadership and Management Services (page images at HathiTrust; US access only)
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