- Mining of Massive Datasets (PDF) — book by Stanford profs, focuses on data mining of very large amounts of data, that is, data so large it does not fit in main memory. Because of the emphasis on size, many of our examples are about the Web or data derived from the Web. Further, the book takes an algorithmic point of view: data mining is about applying algorithms to data, rather than using data to “train” a machine-learning engine of some sort.
- Lessons from Iceland’s Failed Crowdsourced Constitution (Slate) — Though the crowdsourcing moment could have led to a virtuous deliberative feedback loop between the crowd and the Constitutional Council, the latter did not seem to have the time, tools, or training necessary to process carefully the crowd’s input, explain its use of it, let alone return consistent feedback on it to the public.
- Thread a ZigBee Killer? — Thread is Nest’s home automation networking stack, which can use the same hardware components as ZigBee, but which is not compatible, also not open source. The Novell NetWare of Things. Nick Hunn makes argument that Google (via Nest) are taking aim at ZigBee: it’s Google and Nest saying “ZigBee doesn’t work”.
Data science: Where are we going? - DJ Patil, the U.S. government's first Chief Data Scientist, looks at the future of data science at Strata + Hadoop World 2015 in San Jose.
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Radar managing editor