Introduction of Geometric Algebra for Machine Learning and Data Science: A Unified Geometric Framework for Modern Learning Systems - Couverture souple

Setiawan, Sandi

 
9798295882432: Introduction of Geometric Algebra for Machine Learning and Data Science: A Unified Geometric Framework for Modern Learning Systems
Couverture souple
ISBN 13 : 9798295882432
Editeur : Self Publishing LLC, 2026

Synopsis

What if machine learning could be understood geometrically?

This book presents a unified geometric perspective on machine learning, statistics, and data science through the language of geometric algebra.

From linear models and principal component analysis to neural networks, attention mechanisms, and time series systems, modern methods are reinterpreted as geometric transformations in n-dimensional spaces.

Rather than treating techniques as isolated tools, this book reveals the common structure underlying them: movement, orientation, and shape.

- Connects machine learning methods through geometry

- Covers PCA, neural networks, attention, and time series

- Includes PyTorch implementations

- Bridges theory and real-world applications

- Emphasizes intuition over formalism

Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.

Éditeur
Self Publishing LLC
Date d'édition
2026
Langue
anglais
ISBN 13 
9798295882432
Reliure
Tapa blanda
Nombre de pages
240
Coordonnées du fabricant
non disponible
Personne responsable
gpsr@libri.de
gpsr@libri.de

Friedensallee 273
Hamburg
22763
Allemagne