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Scientific computing, machine learning and computer vision for .NET
The Accord.NET Framework provides machine learning, mathematics, statistics, computer vision, computer audition, and several scientific computing related methods and techniques to .NET. The project is compatible with the .NET Framework. NET Standard, .NET Core, and Mono.
math lib for .NET. n-dim arrays, complex numbers, linear algebra, FFT, sorting, cells- and logical arrays as well as 3D plotting classes help developing algorithms on every platform supporting .NET. Sources from SVN, binaries: http://ilnumerics.net
This project consists of two object-oriented implementations of truncated power series (TPSA) for arbitrary order and number of variables. Addition, subtraction, multiplcation, division, and exponentiation are all implemented in the algebra as overloaded operators. They can also compute with maps, a map being an array of TPSA objects representing a mapping of a space into itself.
This is home of the Generic Object Role Modeling Meta-Model (gORMmm). This ORM metamodel is designed as a software independent ORM metamodel for software developers/researchers of first-order logic, conceptual modeling, and artificial intelligence.
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