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Haystax Talks Probabilistic Modeling at MIT

Two Haystax data scientists are headed to the Massachusetts Institute of Technology (MIT) in Boston to deliver a poster-style presentation at the first-ever International Conference on Probabilistic Programming, which runs from October 4-6.

The poster session by Daniel Emaasit and David Jones is entitled Custom PyMC3 nonparametric Bayesian models built on top of the scikit-learn API, and it will run from 12:00-2:40 PM on October 6. It revolves around their contribution to a probabilistic machine learning software package that enables modelers to build flexible and rich probabilistic models using Bayesian nonparametrics, with the ability to quickly and easily deploy them into production systems. These rich, flexible models are currently in use with Haystax’s clients to detect unusual events in user and entity behavior data.

The so-called PROBPROG conference bills itself as “the only conference dedicated to both probabilistic programming research and the practice of probabilistic programming.” More details can be found here.


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