How robust is your path to production? Can you own the end-to-end decision process? From handling input to removing hard-coded parameters, managing versions, and rollout testing, we’ll cover the top best practices for building, testing, and deploying decision models efficiently.
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If you develop decision models in Python, this presentation will save you time (and the added effort of building and maintaining DecisionOps tools). Accelerate development of your optimization models with features for testing, deploying, managing, and collaborating.
What approaches are available to decision scientists and operations researchers to incorporate more randomness and uncertainty into their models? We explore this, ML + OR, and stochastic optimization with Nextmv and Seeker.
Simulate scenarios to answer "what if" questions with your decision model.
In this hands-on workshop designed for operations researchers (decision scientists), developers, and data scientists, participants will get a guided introduction to DecisionOps via the Nextmv platform.
In this step-by-step video, we’ll walk you through deploying a Python OR-Tools traveling salesperson problem (TSP) model using the Nextmv Python template.
