armadillo online with Winfy
We have hosted the application armadillo in order to run this application in our online workstations with Wine or directly.
Quick description about armadillo:
* 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, SuperLU and FFTW libraries
* Useful for machine learning, pattern recognition, signal processing, bioinformatics, statistics, finance, etc.
* Downloads: http: //arma.sourceforge.net/download.html
* Documentation: http: //arma.sourceforge.net/docs.html
* Bug reports: http: //arma.sourceforge.net/faq.html
* Git repo: https: //gitlab.com/conradsnicta/armadillo-code.
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 acceleration via multi-threading
- Used for speeding up NumPy / Python via CARMA: https: //github.com/RUrlus/carma
- Used for machine learning and pattern recognition by MLPACK: https: //mlpack.org/
- Used for numerical optimisation by Ensmallen: https: //ensmallen.org/
Audience: Information Technology, Science/Research, Education, Advanced End Users, Developers, Engineering.
Programming Language: MATLAB, C++.
Categories:
Algorithms, Mathematics, Machine Learning, Computer Vision Libraries
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