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This lecture covers the concept of VC dimension, focusing on practical algorithms like gradient descent and stochastic gradient descent. It explains the definition of convex sets, Lipschitz functions, and the characteristics of convexity. The instructor demonstrates the application of the gradient descent algorithm in convex optimization problems.