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This lecture explores the concept of orthogonality between vectors and vector subspaces. It delves into the notion of orthogonal complements of vector spaces, demonstrating how vectors can be orthogonal to multiple other vectors. The lecture progresses to discuss orthogonal complements of subspaces and proves various properties related to orthogonality. The instructor illustrates how the orthogonal complement of a subspace can be represented by vectors orthogonal to the subspace. Furthermore, the lecture demonstrates the practical implications of orthogonal complements in understanding fundamental subspaces of matrices, highlighting the relationship between the kernel and image of a matrix. The lecture concludes by showcasing the utility of matrix-vector products in calculating inner products efficiently.