9798295882890 - introduction of geometric algebra for machine learning and data science: a unified geometric framework for modern learning systems di setiawan, sandi (12 risultati)
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Hardcover. Condizione: new. Hardcover. 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 mechani…sms, 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 This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Hardcover. Condizione: new. Hardcover. 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 mechani…sms, 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 This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Hardcover. Condizione: new. Hardcover. 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 mechani…sms, 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 This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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Buch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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 componen…t 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.
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Buch. Condizione: Neu. Introduction of Geometric Algebra for Machine Learning and Data Science | A Unified Geometric Framework for Modern Learning Systems | Sandi Setiawan | Buch | Englisch | 2026 | Self Publishing LLC | EAN 9798295882890 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at…]libri[dot]de | Anbieter: preigu Print on Demand.
