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jlo
03-16-2016, 05:29 PM
Announcing the availability of PyNL.

We're pleased to make PyNL 1.0 available to the our IMSL C Numerical Library customers and the Python community.

PyNL is our newly designed Python wrappers are object oriented and include features such as robust error handling, while offering better performance and faster prototype to production cycles. PyNL offers Python wrappers to some of the most desired functions for predictive analytics and machine learning from the IMSL C library. Designed to reduce the prototype to production time many companies face today. Data Science teams build models which are out dated when Engineering completes implementation. With Python wrappers to the IMSL library your Data Science team can use the same powerful Mathematical and Statistical algorithms in Python as the engineering team.

In the near future, we will be granting access to our GitLab repository to create a community in which our IMSL Customers can develop and contribute their own Python wrappers to IMSL C Library.

I look forward to future discussion about PyNL and usage in this forum.

Thank you,
Jennifer Locke
Product Manager
Rogue Wave Software, Inc.