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Understanding exchange network dynamics with Python


This talk covers a use-case for Python ecosystem at IMC for modelling and understanding trade network dynamics, and predicting the results of the changes we introduce. Approaching the problem from different angles, it will include examples of supervised learning, probabilistic models and discrete-event simulations using modules such as scikit-learn, pymc3, and simpy.


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