# Probably Approximately Correct -- a Formal Theory of Learning

DevFeed: [Probably Approximately Correct -- a Formal Theory of Learning](<https://devfeed.tech/articles/probably-approximately-correct-a-formal-theory-of-learning-40337.md>)

Original publisher: [Read original article](<https://www.jeremykun.com/2014/01/02/probably-approximately-correct-a-formal-theory-of-learning/>)

Published: 2014-01-02T18:45:51Z

Content type: tutorial

Language: en

Sources: [Jeremy Kun](<https://devfeed.tech/sources/jeremy-kun.md>)

Topics: [Learning](<https://devfeed.tech/topics/learning.md>), [Machine Learning & Artificial Intelligence](<https://devfeed.tech/topics/machine-learning-artificial-intelligence.md>), [Computer science](<https://devfeed.tech/topics/computer-science.md>), [Mathematics](<https://devfeed.tech/topics/mathematics.md>)

Tags: [learning](<https://devfeed.tech/tags/learning.md>), [learning-theory](<https://devfeed.tech/tags/learning-theory.md>), [machine-learning](<https://devfeed.tech/tags/machine-learning.md>), [mathematics](<https://devfeed.tech/tags/mathematics.md>), [occam-s-razor](<https://devfeed.tech/tags/occam-s-razor.md>), [pac-learning](<https://devfeed.tech/tags/pac-learning.md>), [theory](<https://devfeed.tech/tags/theory.md>)

## AI overview

A mathematical introduction to PAC learning, a foundational framework in computational learning theory. The article develops basic definitions, explains PAC-learnability through interval examples, and places the theory in its historical context.

## Source excerpt

In tackling machine learning (and computer science in general) we face some deep philosophical questions. Questions like, "What does it mean to learn?" and, "Can a computer learn?" and, "How do you define simplicity?" and, "Why does Occam's Razor work? (Why do simple hypotheses do well at modelling reality?)" In a very deep sense, learning theorists take these philosophical questions -- or at least aspects of them -- give them fleshy mathematical bodies, and then answer them with theorems and proofs.