Flow fields are basically a grid of vectors. One can create all kinds of visuals based on it. A stunning example is the Wind Map by Fernanda Viégas and Martin Wattenberg with a fur-like texture visualizing the speed of the wind.
Today I’ll demonstrate how to cook up some unique visuals using flow fields. The standard flow fields look like this, yet I’ll showcase some alternative looks.
A flow field usually consist of (1) a vector field and (2) particle systems. The vector field can be made up of a grid of 2D or 3D vectors. When it comes to 3D, we can view the 2D canvas as a cross-section of a 3D space (more details in this Coding Train video by Daniel Shiffman). …
There are dangers in having models running the world and making decisions from hiring to criminal justice. While it’s ideal to have models that are both interpretable & accurate, many of the popular & powerful algorithms are still black-box.
Among them are highly performant tree ensemble models such as lightGBM, XGBoost, random forest. Knowing their inner workings brings many benefits, including transparency, trust, regulatory compliance and fairness. Or else, one may have to resort to more interpretable yet primitive models.
To make interpretations easier, I built a web app ML-interpreter .
Before diving into the detailed functionalities, here’s a primer on interpretability. …
Strata is a conference focused on data science and enterprise AI/ML. Recently I got a chance to attend and observed some new developments in the field. Here I’ll highlight some talks and concepts I find interesting.
Visual & Hand-drawn queries as data input
In a talk on data science for sports, speaker Patrick Lucey showcased using visual queries to search for patterns that are hard to describe with words. …