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yurchisin committed Dec 3, 2024
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The introductory examples walk you through the process of building a mathematical optimization model.
The basic requirements are that you know Python and have a background in a discipline that uses quantitative methods.

- [GDD 2023: Intro to Gurobipy:](gurobi_days_digital_2023/intro_to_gurobipy)
- [Intro to Gurobipy:](intro_to_gurobipy)
This tutorial was given at the Gurobi Days Digital 2023. It is an introduction to the Gurobi Python API Gurobipy. It walks you through the basics of Gurobipy and explains its usage with some small examples.
- [Intro to Mathematical Optimization Modeling:](milp_tutorial)
This tutorial discusses the basics of mathematical modeling on the example of a simple assignment problem.
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- [Farm Planning](farm_planning)
- [Food Manufacturing](food_manufacturing)
- [Food Program](food_program)
- [GDD 2023: Intro to Gurobipy](gurobi_days_digital_2023/intro_to_gurobipy)
- [Index Tracking](index_tracking)
- [Intro to Gurobipy](intro_to_gurobipy)
- [Intro to Mathematical Optimization Modeling / MILP Tutorial](milp_tutorial)
- [Linear Regression](linear_regression)
- [Logical Design](logical_design)
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# Introduction to Gurobi Python API
This notebook was used for the Gurobi Python API session at Gurobi Days Digital 2023. It will walk you through the basics of the Gurobi Python API.
The video of the session can be watched [here](https://vimeo.com/830685647/c7f9971fda)
This notebook was used for the Gurobi Python API session at Gurobi Days Digital. It will walk you through the basics of the Gurobi Python API.

## View the notebook

[Google Colab Link](https://colab.research.google.com/github/Gurobi/modeling-examples/blob/master/gurobi_days_digital_2023/intro_to_gurobipy/intro_to_gurobipy.ipynb)
[Google Colab Link](https://colab.research.google.com/github/Gurobi/modeling-examples/blob/master/intro_to_gurobipy/intro_to_gurobipy.ipynb)

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For details on licensing or on running the notebooks, see the overview on [Modeling Examples](../../)
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