geographic formatting & spatial dataframes — Last time we installed ArcGIS with minimum fuss and began exploring their mapmaking tools, including raster pixel tilings and searching for more pre-uploaded GIS items online. However, there’s a fairly fundamental rule of data science: The data you want usually isn’t in the place or shape you want it to…

all data has a location if you look hard enough — In the digital age we never lack for information, but often have trouble finding useful knowledge. The answer is nuance. Context makes data truly useful. Add the Pareto Principle: Of all the total information about some topic, 80% of the “useful knowledge” is contained in about 20% of the net…

nature is cruel; statistics is worse — The online dating giant OkCupid runs a blog here on Medium. Every now and then they put out something really fantastic, like this archived article from 2014 that highlighted some fascinating discrepancies on the battlefield of love. It turned some heads and generated some delightfully disruptive graphs, and has since…

black holes and temporal dimensions — As we move through the world, walking or flying in physical space, we also move through time. It’s well argued to be the 4th dimension, for good reason: it takes time to do anything. But then it gets a bit more tricky — we’re probably in something resembling Minkowski Spacetime…

supraspatial decisionmaking — A core data science task is classification: grouping data points into various groups based on certain shared qualities. In a sense, it’s an exercise as old as life itself: as soon as the first protozoan developed sensory organs, it (accidentally) started to act differently based on various sensory stimulus. On…

relationships are complicated — The connections between data can often tell us more than the data itself. Nothing in this world exists in a vacuum — everything is a part of something else, every piece of information is interlinked with other data. Ignore context at your own risk. But since graphs are everywhere —…

unpacking Viviene Clay’s findings in reinforcement learning — I’ve written a few articles on Hierarchical Temporal Memory neural networks, which encode data into Sparse Distributed Representations to make noise-resistant predictions that consider multiple time-steps from the past input feed. The key pioneer of HTM technologies, Numenta, holds weekly research meetings to discuss interesting new theories and advancements in…

tessellation, resolution and you — This is from John Nelson’s Hexperiment. He uses some wicked cool tools to draw hexagonal filters over NASA photos of the United States, further breaks those hexagons down into tessellating diamonds, and makes the whole thing fairly interactive with Chipotle location density data. Last week I spent an entire article…

bees figured this out ages ago — If you’re like me, you’ve always had a strange feeling that bees (much like dolphins) know more than they’re letting on. They know architecture, and communicate navigational information through dance. Their elaborate caste-based hierarchy and collective survival impetus is striking. …