Do any of you do modeling with pymc3 or other Bayesian-oriented packages?

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  • paramonte

    ParaMonte: Parallel Monte Carlo and Machine Learning Library for Python, MATLAB, Fortran, C++, C.

  • Bayesian modeling is at the heart of scientific inference and uncertainty quantification. Whether the industry uses it or not, does not devalue this important approach. If they do not then it is likely that they have not yet realized its significance. But I suspect many do, in collaboration with Academia and they typically use their own specialized high-performance tools for such inferences since their models are far more complex than things that could be implemented via such high-level probabilistic programming languages as pymc3. Incidentally, our lab has developed (and is still developing) a High-Performance serial/parallel package for sampling and integration of Bayesian posteriors which is available from multiple programming languages including C/C++/Fortran/Python/MATLAB/...: https://github.com/cdslaborg/paramonte

  • InfluxDB

    Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

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