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Say you have a stream of items of large and unknown length that we can only iterate over once. Create an algorithm that randomly chooses an item from this stream such that each item is equally likely to be selected.

Algorithms Every Data Scientist Should Know: Reservoir Sampling

In the future, thanks to the Grain, a chip which can be implanted on a hard drive in the brain,every single action that a person makes is recorded and may be played back. Liam, a lawyer, married with a child, suspects that his wife Fi is having a fling with the brash Jonas,whom they meet at a dinner party. After playing clips from his own ‘Grain’ his suspicions are confirmed, and he gets drunk and attacks Jonas, forcing the guilty pair to show him what is in their memory banks. In fact the affair has been going on for months and Liam attacks Jonas, demanding that he erase all memories of Fi from his brain. This, however, does not result in marital reconciliation.

The more I look at videos about Google Glass the more it reminds me of the Grain from “The Entire History of You”, Black Mirror s1e3.

I am not sure I share the enthusiasm with which Google speaks about its project. It’s definitely a technological wonder, but how will it affect personal relationship and society in general? What about split attention? Will we be able to handle the constant information flow?

Sometimes entrance barriers and usage fees (in terms of effort and time in this case) are useful. See for example the tragedy of commons. How will the ability to check Facebook every second of your waking time change your life?

It’s something that’s difficult to explain, has many interpretations,
and the best way to learn it is to do it.

Shamelessly copied from The Apache Way

If it doesn’t, you’re not doing it right.

And on why research is not like sex.

half marathon

Yeeah!

I got excited at the 18th km, when I realized I was going to be able to finish it :)

Reblogged from Melinda Thielbar:

“Any field of study followed by the word “science”, so goes the old wheeze, is not really a science, including computer science, climate science, police science, and investment science.”—Ray Rivera, Forbes Magazine

I too have engaged in my fair share of hand-wringing over “data science”, how the term is used and mis-used, the high quantity of snake oil available, and some generally sloppy practices that seem to be becoming the norm in the internet’s new data-based gold rush.

Read more… 541 more words

On Data Science:
The word Data tells you that I transform raw information into actionable information. The word Scientist emphasizes my commitment to making sure that the analyses my colleagues and I produce are verifiable and repeatable—as all good science should be.
Not sure I agree on the whole argument in the post, but the definition of data science is the best I have seen so far.

I have the pleasure to announce the first workshop on Social News on the Web (SNOW 2013) to be held in Rio de Janeiro, Brazil, co-located with the WWW conference, on May 13th 2013.

In a nutshell:

The workshop provides a forum for presenting novel ideas and discussing future directions in the emerging areas of news searchnews mining, and news recommendation. It especially focuses on the interplay between news content, generated by professional journalists, and social-media content, generated by millions of users in real-time and subject to social-media dynamics.

We also invite contributions on modeling and leveraging user feedback related to news content, as well as contributions on mining news comments. Finally, we invite contributions on the more ambitious topics of citizen journalism and computational journalism. The former studies how citizens can collaborate to collect information, synthesize, edit, verify, and produce their own news stories in a wiki-type paradigm. The latter investigates the use of analysis of web data by professional journalists as an integral part of the news creation process.

The call for papers is out! Please redistribute the call and consider submitting a paper :)

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