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.
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.
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.
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.
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.
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.
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