Bootstrap-Driven Model Diagnostics and Inference in Python/PySpark
Most machine learning workflows rely on a fragile assumption: that a single train/validation split is enough to evaluate a model. Continue reading on Medium »
Could not retrieve the full article text.
Read on Medium AI →Sign in to highlight and annotate this article
Conversation starters
Daily AI Digest
Get the top 5 AI stories delivered to your inbox every morning.
More about
model
Unmathematical features of math
Thanks to @Gurkenglas for being so wrong I decided to write this. (Epistemic status: I consider the following quite obvious and self-evident, but decided to post anyways. [1] ) Mathematics is a social activity done by mathematicians. — Paul Erdős, probably There've been a few attempts to create mathematical models of math. The examples that come to my mind are Gödelian Numbering (GN), Logical Induction (LI), and to some extent Solomonoff Induction (SI). Feel free to suggest more in the comments, but I'll use those as my primary reference points. In this post, I want to contrast them with the way human mathematicians do math by noticing a few features of their process, the ones that are hard to describe with the language of math itself. Those features overlap a lot and reinforce each other,
Knowledge Map
Connected Articles — Knowledge Graph
This article is connected to other articles through shared AI topics and tags.
Discussion
Sign in to join the discussion
No comments yet — be the first to share your thoughts!