Optimization in Python: Case study building a fantasy team for DraftKings

Hi all!

We're going to do a crash course in optimization using python, and then apply it to build an optimal fantasy basketball team (e.g. what would be used for a DraftKings lineup).

Optimization is used across many industries/problems such as for scheduling final exams at a college, GPS routing, deciding where to build warehouses and what it should hold, how to route mail, how to deliver mail on a daily basis, solving sudokus, airlines pricing, etc. There's great sample code for all of this, and in this event we'll talk about where to find it, how to use it, and in our specific example, how to apply it to fantasy basketball.

More specifically we'll work through a this tutorial based on a tutorial provided by Gurobi. Although it's long for an intro, we'll focus on the key tidbits so you can walk away and replicate them on your own problems.

If you're more interested in sudokus, check out this example https://towardsdatascience.com/sudoku-solver-linear-programming-approach-using-pulp-c520cec2f8e8

See you soon,
Mike