I am studying the chapter named Numerical Computation from the deep learning textbook

In the chapter, there is a section named Constrained Optimization. The authors recommended to read the portion of book:Numerical Optimization by Jorge Nocedal Stephen J. Wright related to KKT.

For more information about the KKT approach, see Nocedal and Wright (2006).

I am confused whether I need deep understanding of constrained optimization in-order to understand research papers related to deep learning or not.

Is it recommended to read the entire textbook in detail or is it enough if I can manage (only) to understand the section provided in deep learning textbook?


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