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This lecture covers the process of finding an orthonormal basis using the Gram-Schmidt method, focusing on the projection of vectors onto subspaces and the orthonormalization of bases. The instructor explains step-by-step how to orthonormalize a given base, emphasizing the importance of having an orthonormal basis for practical calculations. The lecture also discusses the concept of orthogonal matrices and their properties, such as being square and having orthonormal columns.