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PyMC3 download for Windows

Free download PyMC3 Windows app to run online win Wine in Ubuntu online, Fedora online or Debian online

This is the Windows app named PyMC3 whose latest release can be downloaded as v5.9.0.zip. It can be run online in the free hosting provider OnWorks for workstations.

Download and run online this app named PyMC3 with OnWorks for free.

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- 7. Download Wine from your Linux distributions software repositories. Once installed, you can then double-click the app to run them with Wine. You can also try PlayOnLinux, a fancy interface over Wine that will help you install popular Windows programs and games.

Wine is a way to run Windows software on Linux, but with no Windows required. Wine is an open-source Windows compatibility layer that can run Windows programs directly on any Linux desktop. Essentially, Wine is trying to re-implement enough of Windows from scratch so that it can run all those Windows applications without actually needing Windows.





PyMC3 allows you to write down models using an intuitive syntax to describe a data generating process. Fit your model using gradient-based MCMC algorithms like NUTS, using ADVI for fast approximate inference — including minibatch-ADVI for scaling to large datasets, or using Gaussian processes to build Bayesian nonparametric models. PyMC3 includes a comprehensive set of pre-defined statistical distributions that can be used as model building blocks. Sometimes an unknown parameter or variable in a model is not a scalar value or a fixed-length vector, but a function. A Gaussian process (GP) can be used as a prior probability distribution whose support is over the space of continuous functions. PyMC3 provides rich support for defining and using GPs. Variational inference saves computational cost by turning a problem of integration into one of optimization. PyMC3's variational API supports a number of cutting edge algorithms, as well as minibatch for scaling to large datasets.


  • Intuitive model specification syntax
  • Powerful sampling algorithms
  • Complex models with thousands of parameters with little specialized knowledge of fitting algorithms
  • ADVI for fast approximate posterior estimation as well as mini-batch ADVI for large data sets
  • Variational inference
  • Computation optimization and dynamic C or JAX compilation

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This is an application that can also be fetched from https://sourceforge.net/projects/pymc3.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.

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