97 projects for "mac framework" with 2 filters applied:

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  • 1
    LUMINOTH

    LUMINOTH

    Deep Learning toolkit for Computer Vision

    LUMINOTH is an open-source deep learning toolkit designed for computer vision tasks, particularly object detection. The framework is implemented in Python and built on top of TensorFlow and the Sonnet neural network library, providing a modular environment for training and deploying detection models. It was created to simplify the process of building and experimenting with deep learning models capable of identifying objects within images. Luminoth includes support for popular object...
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  • 2
    Lihang

    Lihang

    Statistical learning methods (2nd edition) [Li Hang]

    Lihang is an open-source repository that provides educational notes, mathematical derivations, and code implementations based on the book Statistical Learning Methods by Li Hang. The repository aims to help readers understand the theoretical foundations of machine learning algorithms through practical implementations and detailed explanations. It includes notebooks and scripts that demonstrate how key algorithms such as perceptrons, decision trees, logistic regression, support vector...
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  • 3
    When to use TensorFlowSharp

    When to use TensorFlowSharp

    TensorFlow API for .NET languages

    When to use TensorFlowSharp is a .NET binding for the TensorFlow machine learning framework that allows developers to run TensorFlow models directly from C# and other .NET languages. The project exposes TensorFlow’s native C API through a strongly typed interface designed to integrate naturally with the .NET ecosystem. Its primary purpose is to enable developers working in Microsoft-based environments to load trained TensorFlow models and perform inference or additional training within .NET...
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  • 4
    Siamese and triplet learning

    Siamese and triplet learning

    Siamese and triplet networks with online triplet mining in PyTorch

    Siamese and triplet learning is a PyTorch implementation of Siamese and triplet neural network architectures designed for learning embedding representations in machine learning tasks. These types of networks learn to map images into a compact feature space where the distance between vectors reflects the similarity between inputs. Such embeddings are commonly used in applications like face recognition, image similarity search, and few-shot learning. The repository demonstrates how to train...
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  • 5
    Serenata de Amor

    Serenata de Amor

    Artificial Intelligence for social control of public administration

    Serenata de Amor is an open civic technology project that uses data science and artificial intelligence to promote transparency and accountability in public administration. The project was developed by a community of volunteers associated with Open Knowledge Brasil who believe that open data and technology can help citizens monitor government spending. It focuses on analyzing publicly available datasets related to reimbursements claimed by Brazilian congress members in order to detect...
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  • 6
    Machine-Learning-Flappy-Bird

    Machine-Learning-Flappy-Bird

    Machine Learning for Flappy Bird using Neural Network

    Machine-Learning-Flappy-Bird is an educational machine learning project that demonstrates how an artificial intelligence agent can learn to play the Flappy Bird game using neural networks and evolutionary algorithms. The system simulates a population of birds that each possess their own neural network, which acts as a decision-making controller during gameplay. The neural network receives input features representing the bird’s position relative to the next obstacle and determines whether the...
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  • 7
    DMTK

    DMTK

    Microsoft Distributed Machine Learning Toolkit

    The Microsoft Distributed Machine Learning Toolkit (DMTK) is an open-source framework created to support scalable machine learning across distributed computing environments. Developed by Microsoft Research, the toolkit provides infrastructure and algorithms designed to train large models efficiently on clusters of machines rather than a single system. At its core is a parameter-server architecture called Multiverso, which manages model parameters and synchronizes updates across distributed...
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  • 8
    An open source optical flow algorithm framework for scientists and engineers alike.
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  • 9
    libcrn is document image processing library written in C++11 for Linux, Windows, Mac OsX and Google Android. It is a toolbox that allows to create easily software such as OCRs and layout analysis tools.
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  • 10

    JCLALtext

    Text processing module for JCLAL

    JCLALtext is a class library designed to extend the framework JCLAL text tasks. JCLALtext is free, open source and developed with the Java programming language. JCLALtext is distributed under the GNU license. The researcher can use the class library by adding it to your project.
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  • 11
    LPCforSOS is a machine learning framework with a special focus on structured output spaces and pairwise learning. It supports currently multiclass, ordinal, hierarchical, multi-label and label ranking classification settings.
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  • 12
    EpochX
    EpochX is an open source genetic programming framework, specifically for analysing the properties of evolutionary automatic programming. It supports 3 popular representations - Strongly-Typed GP, Context-Free Grammar GP and Grammatical Evolution.
    Downloads: 4 This Week
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  • 13
    This project is devoted to the creation of an open source Error-Correcting Output Codes (ECOC) library for the Machine Learning community. The ECOC framework is a powerful tool to deal with multi-class categorization problems.
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  • 14
    DOGMA is a MATLAB toolbox for discriminative online learning. It implements all the state of the art algorithms in a unique and simple framework. Examples are Perceptron, Passive-Aggresive, ALMA, NORMA, SILK, Projectron, RBP, Banditron, etc.
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  • 15
    The Python Computer Vision Framework is an opened project deisgned for all those interested in computer vision. It aims at making computer vision more easy and structured and matlab-free. It may also be used for other artistic and scientific areas.
    Downloads: 1 This Week
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  • 16
    Program to performing the complete cycle of neural networks analysis: preparing data, choosing neural network (CasCor, MP, LogRegression, PNN), learning of network, monitoring learning state, ROC-analysis, optimization of network parameters using GA.
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  • 17
    Neuroph OCR - Handwriting Recognition
    Neuroph OCR - Handwriting Recognition is developed to recognize hand written letter and characters. It's engine derived's from the Java Neural Network Framework - Neuroph and as such it can be used as a standalone project or a Neuroph plug in.
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  • 18
    A graphical MatLab framework for estimating the parameters of, modeling and simulating static and dynamic linear and polynomial systems in the errors-in-variables context with the intent of comparing various estimation strategies.
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  • 19
    weka outlier is an implementation of outlier detection algorithms for WEKA. CODB (Class Outliers: Distance-Based) Algorithm is the first algorithm developed using WEKA framework.
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  • 20
    Neural - is neural network engine with object-oriented design. Features: - Supports: backpropogation, RPROP algorithms. - Flexible input/outputs framework. - Distributed calculations.
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  • 21
    Highly reusable and extensible Decision-Tree (Max-Gain) framework comprising of comprehensive input-processing and display functionality. Handles nominal, linear, continuous data. For preliminary description, refer - http://sushain.com/blog/archives/
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  • 22
    pySPACE

    pySPACE

    Signal Processing and Classification Environment in Python using YAML

    pySPACE is a modular software for processing of large data streams that has been specifically designed to enable distributed execution and empirical evaluation of signal processing chains. 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...
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