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Dynamic Programming with Python

This website presents a set of lectures on dynamic programming.

Lectures

The lectures cover core dynamic programming concepts and techniques, including:

  • Shortest path problems
  • Job search models
  • Optimal savings and consumption
  • Income fluctuation problems
  • Linear-Quadratic control theory
  • Advanced topics in dynamic programming

Jupyter notebooks

Jupyter notebook versions of each lecture are available for download via the website.

Contributions

To comment on the lectures please add to or open an issue in the issue tracker (see above).

We welcome pull requests!

Please read the QuantEcon style guide first, so that you can match our style.

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Dynamic Programming with Python - QuantEcon Lecture Series

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