Data mining -- Social aspectsSee also what's at your library, or elsewhere.
Broader terms: |
Filed under: Data mining -- Social aspects
Items below (if any) are from related and broader terms.
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)
Filed under: Data mining -- Computer programs
Filed under: Data mining -- Law and legislation -- Study and teaching
Filed under: Data mining -- Law and legislation -- Study and teaching -- United StatesFiled under: Data mining -- Moral and ethical aspects
Filed under: Emigration and immigration -- Social aspects
Filed under: AIDS (Disease) -- Social aspects
Filed under: Academic writing -- Social aspects
Filed under: Aging -- Social aspects- Aging in the Social Space (Białystok-Kraków: Association of Social Gerontologists, 2015), by Łukasz Tomczyk and Andrzej Klimczuk
Filed under: Agroforestry -- Social aspects
Filed under: Animal health -- Social aspects
Filed under: Animals -- Social aspects
Filed under: Arabic language -- Social aspects
Filed under: Artificial intelligence -- Social aspects- Towards a New Enlightenment? A Transcendent Decade (Madrid: BBVA, c2018), contrib. by Francisco González Rodríguez, Martin J. Rees, José M. Sánchez Ron, María Martinón-Torres, Alex Pentland, Sandeep Tiwari, Joanna J. Bryson, Ramon López de Mántaras, José M. Mato, Daniela Rus, Samuel H. Sternberg, Peter Kalmus, Ernesto Zedillo Ponce de León, Victoria Robinson, Barry J. Eichengreen, Michelle Baddeley, Nancy H. Chau, S. M. Ravi Kanbur, Vivien Ann Schmidt, Diana Marie Owen, Yang Xu, Carlo Ratti, and Amos N. Guiora (multiple formats with commentary at bbvaopenmind.com)
- Artificial Communication: How Algorithms Produce Social Intelligence (Cambridge, MA and London: MIT Press, c2022), by Elena Esposito (PDF files with commentary at MIT Press)
- The Future Computed: Artificial Intelligence and its Role in Society (2018), by Microsoft Corporation (PDF with commentary at microsoft.com)
Filed under: Astronautics -- Social aspects
Filed under: Australian languages -- Social aspects
Filed under: Authority -- Social aspects
Filed under: Authorship -- Collaboration -- Social aspects
Filed under: Authorship -- Study and teaching (Higher) -- Social aspects
Filed under: Autism -- Social aspects
Filed under: Automation -- Social aspects
Filed under: Banks and banking -- Social aspects
Filed under: Beauty culture -- Clothing -- Social aspects
Filed under: Big data -- Social aspects
Filed under: Biology -- Social aspects
Filed under: Blogs -- Social aspects
Filed under: Books and reading -- Social aspects
Filed under: Buddhism -- Social aspects
Filed under: Calgary Stampede -- Social aspectsMore items available under broader and related terms at left. |