Showing 6 open source projects for "as built"

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  • 1
    PyMC

    PyMC

    Bayesian Modeling and Probabilistic Programming in Python

    PyMC is a Python library for probabilistic programming focused on Bayesian statistical modeling and machine learning. Built on top of computational tools like Aesara and NumPy, PyMC allows users to define models using intuitive syntax and perform inference using MCMC, variational inference, and other advanced algorithms. It’s widely used in scientific research, data science, and decision modeling.
    Downloads: 0 This Week
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  • 2
    MCPower

    MCPower

    MCPower — simple Monte Carlo power analysis for complex models

    ...It guides users through the full workflow across three tabs: Model setup (formula input with live parsing, CSV data upload with auto-detected variable types, effect size sliders, and correlation editing), Analysis configuration (find power for a given sample size or find the minimum sample size for a target power, with multiple testing correction and scenario analysis), and Results (interactive charts, exportable tables, and auto-generated Python replication scripts). Supports both standard linear models and mixed-effects models. Additional features include analysis history, configurable scenarios, and built-in documentation.
    Downloads: 0 This Week
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  • 3

    statspy

    Python module for statistics built on top of NumPy/SciPy

    Downloads: 0 This Week
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  • 4
    mlpy

    mlpy

    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.
    Downloads: 0 This Week
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  • Build Securely on Azure with Proven Frameworks Icon
    Build Securely on Azure with Proven Frameworks

    Lay a foundation for success with Tested Reference Architectures developed by Fortinet’s experts. Learn more in this white paper.

    Moving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.
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  • 5
    A small simulator for Mendelian genetics, genetic drift, natural selection and random mutations, built on matplotlib and wxpython. A graph will be generated that traces the distribution of genotypes at successive generations.
    Downloads: 0 This Week
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  • 6
    ExoPlanet

    ExoPlanet

    GUI based toolkit for running common Machine Learning algorithms.

    ExoPlanet provides a graphical interface for the construction, evaluation and application of a Machine Learning model in predictive analysis. With the back-end built using the numpy and scikit-learn libraries, as a toolkit, ExoPlanet couples fast and well tested algorithms, a UI designed over the Qt4 framework, and graphs rendered using Matplotlib to provide the user with a rich interface, rapid analytics and interactive visuals. ExoPlanet is designed to have a minimal learning curve, allowing researchers to focus on the applicative aspect of Machine Learning rather than their implementation details. ...
    Downloads: 0 This Week
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