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Inner Products: A Field Guide to Geometry, Similarity, and Stability for Engineering and Machine
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Publisher: Independently Published
Published: Jan 20 2026
Pages: 114
Weight: 0.36
Height: 0.24 Width: 6.00 Depth: 9.00
Language: English
Master the Muscle Memory of Linear Algebra.
In modern engineering-from Machine Learning and NLP to Control Systems and Physics-the inner product is more than just a dot product; it is the fundamental contract you sign with your data. Inner Products by Abhay Singh provides a high-impact, operational guide to understanding the geometry, similarity, and stability of the systems you build.
Using the unique Anubhuti Cycle, this book moves beyond theoretical math into practical muscle memory through:
Conceptual Spines: Coordinate-free intuition for vectors and geometry.
Embodied Experiments: Tactile Do/Notice/Install/Break exercises using everyday objects.
Cross-Domain Transfer: Action patterns applied to Transformers (Attention), Image Processing, Control Costs, and more.
Diagnostic Runbooks: A complete index of failure modes (P0-P7) to detect when your geometry is lying to you.
Whether you are an Solutions Architect, an AI researcher, or a systems engineer, this field guide will teach you to diagnose conditioning issues, handle non-Euclidean transport, and master stability accounting. Stop calculating and start sensing the geometry of your work.
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