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Filed under: Data mining|
Filed under: Data mining -- Computer programs
Filed under: Web search engines
- Mining of Massive Datasets (version 2.1, c2014), by Jurij Leskovec, Anand Rajaraman, and Jeffrey D. Ullman (PDF files with commentary at mmds.org)
- 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 springer.com)
- Python Data Science Handbook (c2016), by Jacob T. Vanderplas (illustrated HTML at Github and jupyter.org)
- 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)
- Cloudera Impala (Sebastopol, CA et al: O'Reilly, c2014), by John Russell (page images at cloudera.com)
- Elasticsearch: The Definitive Guide (Creative Commons edition; c2015), by Clinton Gormley and Zachary Tong (HTML with commentary at elastic.co)
- Untangling the Web: A Guide to Internet Research (unclassified version, slightly redacted; Fort Meade, MD: Center for Digital Content, National Security Agency, 2007), by Robyn Winder, contrib. by Charlie Speight (PDF at nsa.gov)
- 55 Ways to Have Fun With Google: A Cabinet of Search Engine Curiosities, Riddles, Games, and a Little Bit of Usefulness (2006), by Philipp Lenssen (multiple formats with commentary at 55fun.com)
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