An introduction about how to train computers to interact wisely with a stochastic process scenario to maximize certain benefit/reward
8 to 12 h
Markov decision processes, dynamic programming and related algorithms
Fundamental concepts in Reinforcement Learning:
“Foundations of Data Science”, highly advisable “Deep Learning and applications”
Part of ‘Stochastic models and optimization’ in MSc in Data Science, also taught in Data Science Center workshops
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Data Sciencce Center Barcelona Graduate School of Economics Ramón Trías Fargas, 25-27 08005 Barcelona, Spain.
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