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This lecture covers the concept of linear regression using the method of least squares to find the best-fitting line to a set of data points. It explains how to minimize the sum of squared errors and solve the normal equations. The lecture also discusses the conditions for unique solutions and the implications of linearly independent columns in the matrix A.