This lecture covers the sensitivity of solutions in numerical methods, focusing on the sensitivity of linear systems and vector norms. It also discusses matrix norms, the condition number, and provides an example of deblurring images.
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Covers vectorization in Python using Numpy for efficient scientific computing, emphasizing the benefits of avoiding for loops and demonstrating practical applications.
