04-24, 10:30–11:00 (Europe/Berlin), B09
Join us as we guide you through integrating Gurobi and prescriptive analytics into your greater Python ecosystem. We’ll demonstrate model-building patterns based on NumPy and SciPy.sparse data structures and explore how to take advantage of indexed DataFrames and Series in pandas for mathematical model building. You’ll also discover how to use trained regressors from scikit-learn as constraints in optimization models. Join us as we delve into the world of optimization with Gurobi and elevate your workflows.
Gurobi is a prescriptive analytics technology that enables you to make optimal decisions from data. You can use prescriptive analytics to generate optimized decision recommendations, based on real-world variables and constraints. Powered by mathematical models solved by mixed-integer optimization, it enables embedded decision intelligence in all kinds of applications in an industry-agnostic fashion and in any deployment scenario.
Join us as we guide you through integrating Gurobi and prescriptive analytics into your greater Python ecosystem. We’ll demonstrate model-building patterns based on NumPy and SciPy.sparse data structures and explore how to take advantage of indexed DataFrames and Series in pandas for mathematical model building. You’ll also discover how to use trained regressors from scikit-learn as constraints in optimization models. Join us as we delve into the world of optimization with Gurobi and elevate your workflows.
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Expected audience expertise: Python –None
Abstract as a tweet (X) or toot (Mastodon) –Learn how to do Prescriptive Analytics in the Python Ecosystem with Gurobi
Dr. Luce is an experienced researcher in applied mathematics, and author of numerous publications in the fields of numerical linear algebra and optimization. He holds a Ph.D. from Technical University of Berlin.