Artificial Intelligence and Statistics: Epistemological Foundations and Mathematical Relationship · Introduction

Introduction

What this guide covers

Introduction Introduction Advanced Academic Reference

Overview

Introduction
The Relationship between Artificial Intelligence and Statistics From Classical Inference to Statistical and Representation Learning
1. Epistemological Foundations of AI and Statistics
Historical Divergence and Conceptual Convergence
The Two Cultures of Leo Breiman
2. Statistical Learning Theory (statistical learning theory)

Related concepts

Compatible notation

The expression is rendered accessibly, with its LaTeX source preserved below.

\mathcal{R}(h) = \mathbb{E}_{(X,Y) \sim P}[L(h(X), Y)] = \int_{\mathcal{X} \times \mathcal{Y}} L(h(x), y) \, \mathrm{d}P(x,y)

View LaTeX source

\mathcal{R}(h) = \mathbb{E}_{(X,Y) \sim P}[L(h(X), Y)] = \int_{\mathcal{X} \times \mathcal{Y}} L(h(x), y) \, \mathrm{d}P(x,y)