Jerry Yurchisin from Gurobi joins Jon Krohn 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.

Interested in sponsoring a SuperDataScience Podcast episode? Email natalie@superdatascience.com for sponsorship information.

In this episode you will learn:
• The Burrito Optimization Game and mathematical optimization use cases [03:36]
• Key differences between machine learning and mathematical optimization [05:45]
• How mathematical optimization is ideal for real-world constraints [13:50]
• Gurobi’s APIs and the ease of integrating them [21:33]
• How LLMs like GPT-4 can help with optimization problems [39:39]
• Why integer variables are so complex to model [01:02:37]
• NP-hard problems [01:11:01]
• The history of optimization and its early applications [01:26:23]

Additional materials: www.superdatascience.com/813

The Super Data Science Podcast: Machine Learning | AI | Success

813: Solving Business Problems Optimally with Data, with Jerry Yurchisin

The latest machine learning, A.I., and data career topics from across both academia and industry are brought to you by host Dr. Jon Krohn on the Super Data Science Podcast.

As the quantity of data on our planet doubles every couple of years and with this trend set to continue for decades to come, there's an unprecedented opportunity for you to make a meaningful impact in your lifetime. In conversation with the biggest names in the data science industry, Jon cuts through hype to fuel that professional impact.

Whether you're curious about getting started in a data career or you're a deep technical expert, whether you'd like to understand what A.I. is or you'd like to integrate more data-driven processes into your business, we have inspiring guests and lighthearted conversation for you to enjoy.

We cover tools, techniques, and implementation tricks across data collection, databases, analytics, predictive modeling, visualization, software engineering, real-world applications, commercialization, and entrepreneurship − everything you need to crush it with data science.

New tracks tagged #Solving Business Problems with Data