Feb
2015 Mar Publications
All (116) | Courses, Education (9) | Meetings (14) | News, Features (22) | Opinions, Interviews, Reports (47) | Publications (7) | Software (2) | Top Tweets (8) | Webcasts (7)
- More Free Data Mining, Data Science Books and Resources
- Mar 25, 2015.
More free resources and online books by leading authors about data mining, data science, machine learning, predictive analytics and statistics.
- White House report on Big Data and Differential Pricing
- Mar 14, 2015.
White House report examines how companies are using big data and analytics to charge different prices to different customers (price discrimination), looks at both benefits and risks, and concludes that many concerns can be addressed by existing anti-discrimination and consumer protection laws.
- Top Big Data influencers of 2014, according to HadoopSphere
- Mar 13, 2015.
Top big data influencers of 2014 include analysts Mike Gualtieri and Curt Monash, IBM and TDWI media, Spark and Scala products, Ben Lorica @bigdata and Gregory Piatetsky @kdnuggets on social media, Data Collective and AngelList co-founder.
- Machine Learning Table of Elements Decoded
- Mar 11, 2015.
Machine learning packages for Python, Java, Big Data, Lua/JS/Clojure, Scala, C/C++, CV/NLP, and R/Julia are represented using a cute but ill-fitting metaphor of a periodic table. We extract the useful links.
- Chapter Download from “Data Mining Techniques”
- Mar 9, 2015.
Download this chapter from "Data Mining Techniques" (3rd Edition), by Gordon Linoff and Michael Berry, and learn how to create derived variables, which allow the statistical modeling process to incorporate human insights.
- Hurwitz: Cognitive Computing and Big Data Analytics
- Mar 5, 2015.
New book from Judith Hurwitz and associates on Cognitive Computing is a comprehensive guide to the subject, providing both the theoretical and practical guidance technologists need.
- The Elements of Data Analytic Style – checklist
- Mar 4, 2015.
Jeff Leek book "Elements of Data Analytic Style" had a rocket launch, thanks to author course on Coursera. The book includes a useful checklist that can guide beginning data analysts or serve for evaluating data analyses.