Articles liés à Analytical Geometry for Machine Learning: Vectors,...

Analytical Geometry for Machine Learning: Vectors, Transformations, and Spatial Modeling in Applied AI - Couverture souple

Sato, Leonard K.; Van Der Post, Hayden

 
9798252518213: Analytical Geometry for Machine Learning: Vectors, Transformations, and Spatial Modeling in Applied AI
Couverture souple
ISBN 13 : 9798252518213
Editeur : Independently published, 2026

Synopsis

Reactive Publishing

Analytical geometry forms the mathematical foundation behind modern machine learning systems, enabling models to interpret structure, distance, and transformation in high-dimensional space.

This book presents a structured approach to analytical geometry with a focus on its role in machine learning and applied AI. It develops the core concepts required to understand how vectors, coordinate systems, and geometric transformations operate within data-driven models.

Topics include vector operations, linear transformations, coordinate mappings, and spatial representations used in machine learning workflows. Each concept is explored with practical context, connecting geometric intuition to real-world applications such as feature spaces, embeddings, and model optimization.

Designed for readers with a basic background in mathematics, this book bridges the gap between classical geometry and modern computational systems. It provides a clear framework for understanding how spatial reasoning underpins many of the techniques used in machine learning today.

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

Éditeur
Independently published
Date d'édition
2026
Langue
anglais
ISBN 13 
9798252518213
Reliure
Broché
Nombre de pages
500
Éditeur
Schwartz Alice
Coordonnées du fabricant
Manufactured by Amazon on behalf of the author
https://www.amazon.fr/hz/contact-us

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