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

Super Data Science: ML & AI Podcast with Jon Krohn

Conteúdo fornecido por Jon Krohn. Todo o conteúdo do podcast, incluindo episódios, gráficos e descrições de podcast, é carregado e fornecido diretamente por Jon Krohn ou por seu parceiro de plataforma de podcast. Se você acredita que alguém está usando seu trabalho protegido por direitos autorais sem sua permissão, siga o processo descrito aqui https://pt.player.fm/legal.

19d ago 1:43:30

MP3•Home de episódios

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

1127 episódios

#Data Science #Science #Tech #Software Development #Jon Krohn