Lynx Roundup, April 22nd

Data science with Snkia

Resident Scientist Snkia works tirelessly towards robot utopia. These are his findings.

Pretty rad, also includes a link to a longer ebook on the subject.
https://medium.com/@kadek/command-line-tricks-for-data-scientists-c98e0abe5da

https://www.technologyreview.com/s/603366/mathematical-model-reveals-the-patterns-of-how-innovations-arise

https://www.sciencealert.com/scientists-tested-how-much-know-it-alls-actually-know-and-the-results-speak-for-themselves

Never used this, but looks interesting!
https://simonwillison.net/2018/Apr/20/datasette-plugins/

There's a lot of overhead involved in making even pretty trivial blockchain stuff. I made a demo app with Hyperledger last year, and it took a lot just to be able to set it up and have it be viewable.
https://aws.amazon.com/about-aws/whats-new/2018/04/introducing-aws-blockchain-templates/

Very neat bit of...Philosophy of Science? Sociology of Engineering?
https://the-composition.com/the-origins-of-opera-and-the-future-of-programming-bcdaf8fbe960

https://fosterelli.co/executing-gradient-descent-on-the-earth

http://blog.pragmaticengineer.com/distributed-architecture-concepts-i-have-learned-while-building-payments-systems/

https://www.theatlantic.com/magazine/archive/2018/05/barbara-ehrenreich-natural-causes/556859/

I'm definitely in the camp that says AI is an experimental science (particularly Deep Learning stuff, but also generally). But hey, don't take my word for it, here's Turing hisself from the original AI paper: "Machines take me by surprise with great frequency...The view that machines cannot give rise to surprises is due, I believe, to a fallacy to which philosophers and mathematicians are particularly subject. This is the assumption that as soon as a fact is presented to a mind all consequences of that fact spring into the mind simultaneously with it. It is a very useful assumption under many circumstances, but one too easily forgets that it is false." (by the way, if you've never read it, it's extremely readable and absolutely worth reading)
http://aiweirdness.com/post/172894792687/when-algorithms-surprise-us

Along somewhat similar lines (though trying to do the opposite):
https://towardsdatascience.com/interpretable-machine-learning-with-xgboost-9ec80d148d27

I think this really gets at the heart of where quant-y people get crossed up when they have to do certain types of code-y things. As soon as I'm outside of the realm of "doing operations on data", I'm on edge. If I'm, say, interacting with a database from Python, I'm generally doing so in a way that hides as many of the details of connections & cursors as much as possible.
https://twitter.com/kelseyhightower/status/985920494728720384

https://towardsdatascience.com/introduction-to-bayesian-linear-regression-e66e60791ea7

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Center of the Universe Website
Super villain in somebody's action hero movie. Experienced a radioactive freak accident at a young age, which rendered him part-snake and strangely adept at Python.
Author image
Center of the Universe

Super villain in somebody's action hero movie. Experienced a radioactive freak accident at a young age, which rendered him part-snake and strangely adept at Python.