813: Solving Business Problems Optimally with Data — with Jerry Yurchisin
#MathematicalOptimization #OptimizationProblems #DataDrivenDecisionMaking
Jerry Yurchisin from Gurobi joins @JonKrohnLearns to break down mathematical optimization, showing why it often outshines machine learning for real-world challenges. Find out how innovations like NVIDIA’s latest CPUs are speeding up solutions to problems like the Traveling Salesman in seconds.
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In this episode you will learn:
• [00:00:00] Introduction
• [00:02:06] The Burrito Optimization Game and mathematical optimization use cases
• [00:04:15] Key differences between machine learning and mathematical optimization
• [00:12:20] How mathematical optimization is ideal for real-world constraints
• [00:20:03] Gurobi’s APIs and the ease of integrating them
• [00:38:07] How LLMs like GPT-4 can help with optimization problems
• [01:01:05] Why integer variables are so complex to model
• [01:09:31] NP-hard problems
• [01:24:51] The history of optimization and its early applications
Additional materials: https://www.superdatascience.com/813