Deploy and run a Statsmodels ML regressor, Gurobipy price avocado optimizer, and end-to-end decision workflow on Nextmv via a Jupyter Notebook on Google Colab. Plus, visualize results using Plotly and perform a scenario test to determine relationship between price and profit.
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Learn how to solve mixed integer programming (MIP) problems with Google’s OR-Tools for use cases like scheduling, order fulfillment, packing and more. Then promote an updated model to production using CI/CD.
Automating on-demand logistics operations for scale, customization, and iteration is easier than you might think. Learn how to build, test, and deploy models for demand forecasting, shift scheduling, and route creation.
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Learn how to integrate a new or existing OR-Tools model into production systems using Nextmv and its infrastructure, testing capabilities, and collaboration features to create a repeatable workflow to production.
With the Nextmv Shift Scheduling app, you can start automating shift scheduling decisions in minutes.
Launch your OR-Tools model into production as a decision microservice with a simple copy/paste in Python using the Nextmv OR-Tools integration.
