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Beautiful Lorenz chaos graph.

[Illustration: Markus Hofko]

Natural Language Processing in Ruby

#NLP #ruby

Beauty of Mathematics

#math

Re-learning JavaScript

http://yuiblog.com/crockford/

http://stackoverflow.com/questions/11246/best-resources-to-learn-javascript

https://developer.mozilla.org/en-US/docs/Web/JavaScript/A_re-introduction_to_JavaScript?redirectlocale=en-US&redirectslug=JavaScript%2FA_re-introduction_to_JavaScript

http://wtfjs.com/

http://addyosmani.com/resources/essentialjsdesignpatterns/book/

http://wtfjs.com/2013/02/12/obfuscated-fibonacci

#javascript

The Big List of D3.js Examples

http://christopheviau.com/d3list/ http://www.jasondavies.com/animated-quasicrystals/

Sell before you Build

#bayesian

To what extent should one trust a statement that a program is free of Trojan horses? Perhaps it is more important to trust the people who wrote the software.

Hack Your Motivation

Nothing is better than being truly motivated by an exciting project. But if you're stuck, here are some things to try out that can give a temporary boost. The common theme among these is switching your perspective from thinking about your project as a huge endeavor and instead concentrating on the next practical step.

#hack your motivation

Source: http://vis.berkeley.edu/papers/animated_transitions/

#animated transitions #graphs

Abstract:

We explain why, if we live in a simulated reality, we might expect to see occasional glitches and small drifts in the supposed constants and laws of Nature over time.

#simulation argument

Perhaps its most startling lesson is that there is a significant probability that you are living in computer simulation. I mean this literally: if the simulation hypothesis is true, you exist in a virtual reality simulated in a computer built by some advanced civilisation. Your brain, too, is merely a part of that simulation. What grounds could we have for taking this hypothesis seriously?

#reality #simulation #argument

https://www.udacity.com/course/cs212

#algorithms

Tinkerbell map

The *Tinkerbell map* is a discrete-time dynamical system given by: [image: x_{n+1}=x_n^2-y_n^2+ax_n+by_n,][image: y_{n+1}=2x_ny_n+cx_n+dy_n,]

Some commonly used values of a, b, c, and d are

- [image: a=0.9, b=-0.6013, c=2.0, d=0.50] - [image: a=0.3, b=0.6000, c=2.0, d=0.27]

Like all chaotic maps, the Tinkerbell Map has also been shown to have periods; after a certain number of mapping iterations any given point shown in the map to the right will find itself once again at its starting location.

More good stuff here http://softology.com.au/tutorials/attractors2d/tutorial.htm

#chaotic behaviour

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