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MaTEx is a collection of parallel machine learning and data mining (MLDM) algorithms, targeted for desktops, supercomputers and cloud computing systems.

MaTEx primarily provides high performance implementations of Deep Learning algorithms . The current implementations use MPI for inter-node communication and multi-threading/CUDA (cuDNN) for intra-node execution, by using Google TensorFlow as the baseline.

MaTEx also supports K-means, Spectral Clustering algorithms for Clustering, Support Vector Machines, KNN algorithms for Classification, and FP-Growth for Association Rule Mining.