In a ML context kernel would probably be understood as a way to quantify similarity between different examples: https://en.m.wikipedia.org/wiki/Kernel_method
But it was hilarious to see how many other "normal" meanings came up in the comments.
But it was hilarious to see how many other "normal" meanings came up in the comments.
Hell, in math, normal even has multiple meanings. You have the normal distribution and surface normals for example