Very interesting thoughts about the fact that sometimes it pays more to add more data rather than fine-tuning the weights on your fancy machine-learning algorithm.

Second part of the very good article about having more data vs. better algorithms

A visualization of data gathered on 210 million public Facebook profiles that shows the information by location, with connections drawn between places that share friends. For example, a lot of people in LA have friends in San Francisco, so there’s a line between them.

Datasets about almost everything !

R is an open source implementation of the S-Plus language. It is freely available and is licensed under the GPL. The language simplifies many statistical computations and can be a powerful tool.

An overview of different techniques to extract actual content from web pages.

Examples of using elasticsearch and protovis to provide with useful and good looking visualizations.

Big PDF of useful things about data engineering, data mining, workflows, etc.

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