723: Mathematical Optimization, with Jerry Yurchisin
Super Data Science: ML & AI Podcast with Jon Krohn
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Mathematical Optimization in Business
This chapter explores the significance of mathematical optimization in business decision-making, highlighting the contrast between gradient descent in machine learning and Groby solvers in ensuring optimal solutions. It discusses various techniques such as linear programming and mixed integer programming, emphasizing their role in solving complex machine learning problems efficiently. The chapter also delves into the theoretical aspects of convex problems and the simplex method for achieving optimal solutions in linear programming scenarios.
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