Disk image and hypercard slides for our EnthusiastiCon 2020 talk on implementing KMeans in K
Data Science methods are not normally written in K. But what if they were?
K is a high-performance programming language popular in finance, but rarely seen elsewhere. KMeans is a classic machine learning algorithm which partitions data into homogeneous groups.
While K is much less well known among data scientists than Python, it shares a common heritage with NumPy as both were strongly influenced by APL.
By showing how KMeans can be written in K, we’ll demonstrate how the features of this esoteric language encourage poetic expression of mathematical concepts and more intuitive interaction with data.
