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Introduction of Geometric Algebra for Machine Learning and Data Science: A Unified Geometric Framework for Modern Learning Systems by Sandi Setiawan at Abbey's Bookshop,
Introduction of Geometric Algebra for Machine Learning and Data Science: A Unified Geometric Framework...
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Sandi Setiawan

Introduction of Geometric Algebra for Machine Learning and Data Science

A Unified Geometric Framework for Modern Learning Systems

Sandi Setiawan

$51.95   $43.78

Paperback

Hardback

Not in-store but you can order this
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English
Self Publishing LLC
06 May 2026
Geometry; Machine learning
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
By:  
Imprint:   Self Publishing LLC
Dimensions:   Height: 279mm,  Width: 216mm,  Spine: 13mm
Weight:   567g
ISBN:   9798295882432
Pages:   240
Publication Date:  
Audience:   General/trade ,  ELT Advanced
Format:   Paperback
Publisher's Status:   Active

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