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neon is Intel's reference deep learning framework committed to best performance on all hardware. Designed for ease-of-use and extensibility. For fast iteration and model exploration, neon has the fastest performance among deep learning libraries (2x speed of cuDNNv4, see benchmarks).

deep-learning neon mkl performance fast neural-networkGosl is a Go library to develop Artificial Intelligence and High-Performance Scientific Computations. The library tries to be as general and easy as possible. Gosl considers the use of both Go concurrency routines and parallel computing using the message passing interface (MPI). Gosl has several modules (sub-packages) for a variety of tasks in scientific computing, image analysis, and data post-processing.

scientific-computing visualization linear-algebra differential-equations sparse-systems plotting mkl parallel-computations computational-geometry graph-theory tensor-algebra fast-fourier-transform eigenvalues eigenvectors hacktoberfest machine-learning artificial-intelligence optimization optimization-algorithms linear-programmingArmadillo: fast C++ library for linear algebra & scientific computing - http://arma.sourceforge.net

linear-algebra matrix matrix-functions linear-algebra-library statistics matlab blas lapack hpc scientific-computing mkl machine-learning armadillo openmp gaussian-mixture-models cpp11 vector sparse-matrix expression-template matrix-factorizationWelcome to my repo to build Data Science, Machine Learning, Computer Vision, Natural language Processing and Deep Learning packages from source. My Data Science environment is running from a LXC container so Tensorflow build system, bazel, must be build with its auto-sandboxing disabled.

archlinux data-science machine-learning deep-learning package tensorflow scikit-learn mxnet opencv nervana pandas cudnn cuda pytorch spacy natural-language-processing natural-language-understanding xgboost lightgbm mklThese Fortran libraries are copied and only the Makefiles (not the code) lightly modified to build easily with Gfortran on a wide variety of systems including Linux, MacOS and Windows. Please respect the various licenses of these libraries. The MIT license applies only to our convenience build scripts. Look under cmake/Modules/Find_____.cmake to conveniently link these libraries to your project.

lapack95 cmake mkl fortran2018 fortran2008 modern-fortran scalapack fortran-library gfortran intel metis scotch
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