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Connecting Reinforcement Learning to Simulation Software

The Data Exchange Podcast: Max Pumperla on why he’s bullish on Tune, training data scientists, and contributing to open source.


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In this episode of the Data Exchange I speak with Max Pumperla, deep learning engineer at Pathmind1 and a contributor to many open source projects in data science and machine learning.  Max is speaking on applications of reinforcement learning to simulation problems at the upcoming Ray Summit, a free virtual conference scheduled for Sep 30th and Oct 1st.  Earlier this year I had Pathmind’s CEO Chris Nicholson on this podcast and he described how reinforcement learning might play a role in simulation problems. In this episode, Max provides an update and a technical description of how Pathmind uses reinforcement learning, RLLib, and Tune, to help users of AnyLogic, a widely used software for simulations in business applications.

Scalable machine learning, scalable Python, for everyone: Join Max Pumperla, David Patterson, Michael Jordan, Oriol Vinyals, Manuela Veloso, Azalia Mirhoseini, Zoubin Ghahramani, Wes McKinney, Ion Stoica, Raluca Popa and many other speakers at the first Ray Summit, a FREE virtual conference which takes place Sep 30th and Oct 1st.

Since Max is the maintainer of Hyperopt, we also discussed the state of open source tools for hyperparameter tuning:

Our conversation opened with teaching data science. Max has just agreed to serve as a part-time faculty member at a new data science program at IUBH in Germany.  I asked him to describe the types of courses he plans to teach and how he plans to prepare his students for jobs in industry.

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[1] I am an advisor to Pathmind.

[Image by Hillary Wimsatt from Pixabay ]

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