Pseudoinverse
Chapter 8: Singular Value Decomposition (SVD) — Pseudoinverse
From the book
Chapter 8: Singular Value Decomposition (SVD). In the chapter mind map this icon labels Pseudoinverse: $A^\dagger = V\Sigma^\dagger U^\top$. The discussion below is excerpted and lightly edited from § Opening in Mathematics for AI and Machine Learning.
Singular Value Decomposition: the fundamental matrix factorization for data analysis
What this drawing shows
What you see. Represents the generalized inverse used for least-squares and rank-deficient systems.
In the mind map. Chapter 8 — Pseudoinverse. See From the book above for definitions, figures, and worked examples.
Where to read next
Read the full definitions, figures, and worked examples in Chapter 8: Singular Value Decomposition (SVD) — see the mind-map node Pseudoinverse.