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  • Get your Apps to customers 5x faster with RAD Studio. Get your Apps to customers 5x faster with RAD Studio. Icon
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  • Open source. Easy to use. Proven. Complete. Open source. Easy to use. Proven. Complete. Icon
    Open source. Easy to use. Proven. Complete. Icon

    End to end big data in a massively scalable super computing platform that enables you spend less time formatting data and more time analyzing it.

    Discover HPCC Systems - the truly open source big data solution that allows you to quickly process, analyze and understand large data sets, even data stored in massive, mixed-schema data lakes. Designed by data scientists, HPCC systems is a complete integrated solution from data ingestion and data processing to data delivery. The free online introductory courses and a robust developer community allow you to get started quickly.
  • mlpy Icon


    Machine Learning Python

    mlpy is a Python module for Machine Learning built on top of NumPy/SciPy and of GSL. mlpy provides high-level functions and classes allowing, with few lines of code, the design of rich workflows for classification, regression, clustering and feature selection. mlpy is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License version 3. mlpy is available both for Python >=2.6 and Python 3.X.

    Downloads: 162 This Week Last Update: See Project
  • runjags

    The 'runjags' R package and standalone JAGS extension module

    This package provides high-level interface utilities for MCMC models via Just Another Gibbs Sampler (JAGS), facilitating the use of parallel (or distributed) processors for multiple chains, automated control of convergence and sample length diagnostics, and evaluation of the performance of a model using drop-k validation or against simulated data. Template model specifications can be generated using a standard lme4-style formula interface to assist users less familiar with the BUGS syntax. A JAGS extension module provides additional distributions including the Pareto family of distributions, the DuMouchel prior and the half-Cauchy prior.

    Downloads: 4 This Week Last Update: See Project
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