Publisher Description
* Fast C++ library for linear algebra (matrix maths) and scientific computing
* Easy to use functions and syntax, deliberately similar to Matlab / Octave
* Uses template meta-programming techniques to increase efficiency
* Provides user-friendly wrappers for OpenBLAS, Intel MKL, LAPACK, ATLAS, ARPACK and SuperLU libraries
* Useful for machine learning, pattern recognition, signal processing, bioinformatics, statistics, finance, etc.
* Downloads:
* Documentation:
* Bug reports:
* Git repo:
Features
- Easy to use - has many MATLAB like functions
- Useful for prototyping directly in C++
- Useful for conversion of research code into production environments
- Permissively licensed - can be used in proprietary software and products
- Used for machine learning, pattern recognition, computer vision, signal processing, bioinformatics, statistics, finance, etc
- Efficient classes for vectors, matrices, cubes (1st, 2nd, 3rd order tensors)
- Supports dense and sparse matrices
- Fast singular value decomposition (SVD), eigen decomposition, QR, LU, Cholesky, FFT
- Clustering using k-means and Gaussian Mixture Models (GMM)
- Automatic vectorisation of expressions (SIMD)
- Contiguous and non-contiguous submatrices
- Automatically combines several operations into one to increase speed and efficiency
- Read/write data in CSV files
- Automatically uses OpenMP for speedups
- Used for machine learning by MLPACK:
- Used for numerical optimisation by Ensmallen: