A concise overview of Cholesky decomposition: what it is, why it only applies to Hermitian positive definite matrices, and how factoring A into a lower triangular L and its conjugate transpose enables efficient solutions for linear systems, least squares, and state estimation. We'll explore the geometric intuition, key algorithms, numerical stability, and practical considerations, with a preview of Part 2 on real-world applications.

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