Machine Learning: Unsupervised Learning and Latent Structure Analysis — Advanced Reference · Introduction

Introduction

What this guide covers

A comprehensive and mathematically rigorous treatise on partitioning algorithms, density, linear/non-linear dimensional reduction, and latent variable models for data scientists.

Overview

Topics covered

Introduction
Unsupervised Learning and Latent Structure Analysis
Mathematical Foundations of Unsupervised Learning
Grouping (Clustering)
Dimensional Reduction
Generative Modeling

Related concepts

Main connections

Compatible notation

Mathematical sample in LaTeX

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

\lim_{d \to \infty} \frac{\text{Dist}_{\max} - \text{Dist}_{\min}}{\text{Dist}_{\min}} = 0

View LaTeX source

\lim_{d \to \infty} \frac{\text{Dist}_{\max} - \text{Dist}_{\min}}{\text{Dist}_{\min}} = 0