Streamline Application Development With the IMSL Python Library

The IMSL Python Numerical Library (PyNL) provides mathematical and statistical functionality for building advanced a wide range of applications in Python. Built on the IMSL C Numerical Library, PyNL brings over 40 years of numerical expertise, rigorous testing, and native performance to the Python environment.

High Return on Investment

Save on costs associated with development, documentation, testing, and maintenance.

Tested and Dependable

Based on the IMSL C Library, PyNL is a highly accurate and performant solution.

Comprehensive and Robust

Developers can quickly add robust and comprehensive functionality with PyNL.

Advanced Mathematical and Statistical Functionality

The IMSL Python Library features advanced embeddable mathematical and statistical algorithms used across a wide variety of applications, including: modeling airplane flight dynamics, weather prediction, innovative study of the human genome, stock market behavior forecasts, and investment portfolio optimization.

IMSL Python for Neural Networks

Whether it’s forecasting, classification, or statistical pattern recognition, IMSL Python neural network functions can help data analysts produce reliable forecasts even with messy and minimal data.

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IMSL Python Libraries for Data Analysis and Data Science

With algorithms and functions for cluster analysis, Eigensystem analysis, and algorithms that help to establish correlations between data sets, the IMSL Python Library can be used for data mining, text mining, and bioinformatic applications.

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IMSL Python for Machine Learning

With algorithms and functions like decision tree, regression, and more, the IMSL Python Library can be applied to add machine learning functionality to Python applications.

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About the IMSL Library for Python

The IMSL Library for Python is a library of Python functions useful for programming in a wide range of applications ranging from scientific, to engineering, to business.

IMSL for Python Variants

PyNL is one member of a family of numerical libraries targeting various development environments. PyNL specifically targets the C implementation of Python (CPython). For Cython projects, we recommend using the IMSL Library for C. For Jython, we recommend using the IMSL Library for Java.

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IMSL Python Library Key Features

The IMSL Libraries, including the IMSL Python Library, are regarded as the most sophisticated, flexible, scalable and highly accessible technology available for numerical analysis in the most important mainstream programming environments in use today.

Accessible, Intuitive, Consistent

With descriptive and consistent function names, the IMSL Python Library is accessible and intuitive for developers and data scientists alike.

Reduce Development Costs

Save time and money on design, development, documentation, testing, and maintenance with proven IMSL algorithms and functions.

Performant and Scalable

With support for multi-thread processes and thoroughly tested functions and algorithms, the IMSL Python Library is high performance ready.

Clear Diagnostic Error Messaging

With informative and clear error messaging, developers can quickly get to work on fixing the issue instead of trying to find it.

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See how the IMSL Python Library works on your application with a free 30-day trial.

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