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    MongoDB Atlas runs apps anywhere

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  • 1
    OBLITERATUS

    OBLITERATUS

    OBLITERATE THE CHAINS THAT BIND YOU

    ...The toolkit provides a full pipeline for probing, analyzing, and modifying model behavior, including visualization tools that help researchers understand where and how refusal mechanisms are encoded. It supports multiple analytical methods such as PCA and SVD to locate these behavioral directions within model layers.
    Downloads: 59 This Week
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  • 2
    ml.js

    ml.js

    Machine learning tools in JavaScript

    This library is a compilation of the tools developed in the mljs organization. It is mainly maintained for use in the browser. If you are working with Node.js, you might prefer to add to your dependencies only the libraries that you need, as they are usually published to npm more often. We prefix all our npm package names with ml- (eg. ml-matrix) so they are easy to find.
    Downloads: 4 This Week
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  • 3
    MatlabMachine

    MatlabMachine

    Machine learning algorithms

    Matlab-Machine is a comprehensive collection of machine learning algorithms implemented in MATLAB. It includes both basic and advanced techniques for classification, regression, clustering, and dimensionality reduction. Designed for educational and research purposes, the repository provides clear implementations that help users understand core ML concepts.
    Downloads: 1 This Week
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  • 4
    Linfa

    Linfa

    A Rust machine learning framework

    linfa aims to provide a comprehensive toolkit to build Machine Learning applications with Rust. Kin in spirit to Python's scikit-learn, it focuses on common preprocessing tasks and classical ML algorithms for your everyday ML tasks.
    Downloads: 0 This Week
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    Enterprise-grade ITSM, for every business

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    AutoMLPipeline.jl

    AutoMLPipeline.jl

    Package that makes it trivial to create and evaluate machine learning

    ...To illustrate, here is a pipeline expression and evaluation of a typical machine learning workflow that extracts numerical features (numf) for ica (Independent Component Analysis) and pca (Principal Component Analysis) transformations, respectively, concatenated with the hot-bit encoding (ohe) of categorical features (catf) of a given data for rf (Random Forest) modeling.
    Downloads: 2 This Week
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  • 6
    Streamline Analyst

    Streamline Analyst

    AI agent that streamlines the entire process of data analysis

    Streamline Analyst is a cutting-edge, open-source application powered by Large Language Models (LLMs) designed to revolutionize data analysis. This Data Analysis Agent effortlessly automates all the tasks such as data cleaning, preprocessing, and even complex operations like identifying target objects, partitioning test sets, and selecting the best-fit models based on your data. With Streamline Analyst, results visualization and evaluation become seamless.
    Downloads: 0 This Week
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  • 7
    Accord.NET Framework

    Accord.NET Framework

    Scientific computing, machine learning and computer vision for .NET

    The Accord.NET Framework provides machine learning, mathematics, statistics, computer vision, computer audition, and several scientific computing related methods and techniques to .NET. The project is compatible with the .NET Framework. NET Standard, .NET Core, and Mono.
    Downloads: 0 This Week
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  • 8

    EMGU Face Recognition

    Using EMGU to perform Principle Component Analysis (PCA)

    ...Face Recognition has always been a popular subject for image processing and this article builds upon the good work by Sergio Andrés Gutiérrez Rojas and his original article (codeproject). The reason that face recognition is so popular is not only it’s real world application but also the common use of principle component analysis (PCA). PCA is an ideal method for recognising statistical patterns in data. The popularity of face recognition is the fact a user can apply a method easily and see if it is working without needing to know to much about how the process is working.
    Downloads: 0 This Week
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  • 9
    Stanford Machine Learning Course

    Stanford Machine Learning Course

    machine learning course programming exercise

    The Stanford Machine Learning Course Exercises repository contains programming assignments from the well-known Stanford Machine Learning online course. It includes implementations of a variety of fundamental algorithms using Python and MATLAB/Octave. The repository covers a broad set of topics such as linear regression, logistic regression, neural networks, clustering, support vector machines, and recommender systems. Each folder corresponds to a specific algorithm or concept, making it easy...
    Downloads: 3 This Week
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  • 10
    Very basic cellular automaton implementation in C#. Based upon the "Togetherness" algorithm described at http://www.hermetic.ch/pca/tg.htm.
    Downloads: 0 This Week
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  • 11
    ...Backpropagation and RPROP are available as training algorithms. Design goals: speed of execution when calculating the output to new data, and quality of training (preprocessing: PCA).
    Downloads: 0 This Week
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  • 12
    WHAY is a Video-based Face Recognition tool written in MATLAB. It aims to exploits PCA recognizing as better as possible and tests the limits of this approach.
    Downloads: 0 This Week
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