Showing 6 open source projects for "svm"

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  • 1
    OSX-KVM

    OSX-KVM

    Run macOS on QEMU/KVM

    ...The project can fetch installers for multiple macOS generations, prepare installation media, and guide users through the complete virtual machine setup. It supports Intel VT-x and AMD SVM hosts, although newer macOS releases impose additional CPU instruction requirements. Included resources cover networking, libvirt, offline installation, headless operation, diagnostics, cloud environments, and GPU passthrough experiments. The repository is useful for macOS testing, development, research, and build-farm scenarios on compatible hardware. ...
    Downloads: 4 This Week
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  • 2
    m2cgen

    m2cgen

    Transform ML models into a native code

    m2cgen (Model 2 Code Generator) - is a lightweight library that provides an easy way to transpile trained statistical models into a native code (Python, C, Java, Go, JavaScript, Visual Basic, C#, PowerShell, R, PHP, Dart, Haskell, Ruby, F#, Rust, Elixir). Transform ML models into a native code (Java, C, Python, Go, JavaScript, Visual Basic, C#, R, PowerShell, PHP, Dart, Haskell, Ruby, F#, Rust) with zero dependencies. Some models force input data to be particular type during prediction phase...
    Downloads: 0 This Week
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  • 3
    Machine-Learning

    Machine-Learning

    kNN, decision tree, Bayesian, logistic regression, SVM

    Machine-Learning is a repository focused on practical machine learning implementations in Python, covering classic algorithms like k-Nearest Neighbors, decision trees, naive Bayes, logistic regression, support vector machines, linear and tree-based regressions, and likely corresponding code examples and documentation. It targets learners or practitioners who want to understand and implement ML algorithms from scratch or via standard libraries, gaining hands-on experience rather than relying...
    Downloads: 0 This Week
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  • 4
    Active Learning

    Active Learning

    Framework and examples for active learning with machine learning model

    ...It includes several established active learning strategies such as uncertainty sampling, k-center greedy selection, and bandit-based methods, while also allowing for custom algorithm implementations. The framework integrates with both classical machine learning models (SVM, logistic regression) and neural networks.
    Downloads: 3 This Week
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    Build Agents and Models on One Platform

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  • 5

    Face Recognition

    World's simplest facial recognition api for Python & the command line

    Face Recognition is the world's simplest face recognition library. It allows you to recognize and manipulate faces from Python or from the command line using dlib's (a C++ toolkit containing machine learning algorithms and tools) state-of-the-art face recognition built with deep learning. Face Recognition is highly accurate and is able to do a number of things. It can find faces in pictures, manipulate facial features in pictures, identify faces in pictures, and do face recognition on a...
    Downloads: 1 This Week
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  • 6
    pySPACE

    pySPACE

    Signal Processing and Classification Environment in Python using YAML

    ...Various signal processing algorithms (so called nodes) are available within the software, from finite impulse response filters over data-dependent spatial filters (e.g. CSP, xDAWN) to established classifiers (e.g. SVM, LDA). pySPACE incorporates the concept of node and node chains of the MDP framework. Due to its modular architecture, the software can easily be extended with new processing nodes and more general operations. Large scale empirical investigations can be configured using simple text- configuration files in the YAML format, executed on different (distributed) computing modalities, and evaluated using an interactive graphical user interface. ...
    Downloads: 0 This Week
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