We will focus on problems that arise in machine learning and modern data analysis paying attention to concerns about complexity robustness and implementation in these domains we will also see how tools from convex optimization can help tackle non convex optimization problems common in practice course notes course notes will be publicly . This book provides a basic initial resource introducing science and engineering students to the field of optimization it covers three main areas mathematical programming calculus of variations and optimal control highlighting the ideas and concepts and offering insights into the importance of optimality conditions in each area. The theory of the best approximation is applicable in a variety of problems arising in nonlinear functional analysis and optimization this book highlights interesting aspects of nonlinear analysis and optimization together with many applications in the areas of physical and social sciences including engineering
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