Showing 21 open source projects for "python neural network"

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  • 1
    Python Outlier Detection

    Python Outlier Detection

    A Python toolbox for scalable outlier detection

    ...PyOD has multiple neural network-based models, e.g., AutoEncoders, which are implemented in both PyTorch and Tensorflow. PyOD contains multiple models that also exist in scikit-learn. It is possible to train and predict with a large number of detection models in PyOD by leveraging SUOD framework. A benchmark is supplied for select algorithms to provide an overview of the implemented models.
    Downloads: 8 This Week
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  • 2
    PRML

    PRML

    PRML algorithms implemented in Python

    PRML repository is a respected and well-maintained project that implements the foundational algorithms from the famous textbook Pattern Recognition and Machine Learning by Christopher M. Bishop, providing a practical and accessible Python reference for both students and professionals. Rather than just summarizing concepts, the repository includes working code that demonstrates linear regression and classification, kernel methods, neural networks, graphical models, mixture models with EM algorithms, approximate inference, and sequential data methods — all following the book’s structure and notation. ...
    Downloads: 0 This Week
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  • 3
    DomainBed

    DomainBed

    DomainBed is a suite to test domain generalization algorithms

    DomainBed is a PyTorch-based research suite created by Facebook Research for benchmarking and evaluating domain generalization algorithms. It provides a unified framework for comparing methods that aim to train models capable of performing well across unseen domains, as introduced in the paper In Search of Lost Domain Generalization. The library includes a wide range of well-known domain generalization algorithms, from classical baselines such as Empirical Risk Minimization (ERM) and...
    Downloads: 1 This Week
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  • 4
    Evolutionary Algorithm

    Evolutionary Algorithm

    Evolutionary Algorithm using Python

    ...Users can explore basic genetic algorithm setups, match phrase examples, pathfinding challenges, and microbial GA variants, as well as evolution strategy approaches like NES. The project also links classical evolutionary approaches with neural networks, illustrating how evolution can be used for model training in reinforcement learning and supervised contexts.
    Downloads: 0 This Week
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  • 5
    MLPACK is a C++ machine learning library with emphasis on scalability, speed, and ease-of-use. Its aim is to make machine learning possible for novice users by means of a simple, consistent API, while simultaneously exploiting C++ language features to provide maximum performance and flexibility for expert users. * More info + downloads: https://mlpack.org * Git repo: https://github.com/mlpack/mlpack
    Downloads: 0 This Week
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  • 6
    Real-ESRGAN

    Real-ESRGAN

    Real-ESRGAN aims at developing Practical Algorithms

    ...It emphasizes usability with utilities that handle alpha channels, gray/16-bit images, and tiled inference for large inputs, and can be run via Python scripts or portable executables.
    Downloads: 199 This Week
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  • 7
    Consistent Depth

    Consistent Depth

    We estimate dense, flicker-free, geometrically consistent depth

    Consistent Depth is a research project developed by Facebook Research that presents an algorithm for reconstructing dense and geometrically consistent depth information for all pixels in a monocular video. The system builds upon traditional structure-from-motion (SfM) techniques to provide geometric constraints while integrating a convolutional neural network trained for single-image depth estimation. During inference, the model fine-tunes itself to align with the geometric constraints of a specific input video, ensuring stable and realistic depth maps even in less-constrained regions. This approach achieves improved geometric consistency and visual stability compared to prior monocular reconstruction methods. ...
    Downloads: 0 This Week
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  • 8
    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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  • 9
    leet

    leet

    Leet is CCEx's software application for on-the-fly encryption (OTFE).

    The name leet stands for "Linux exquisite encryption tool", it will be a software application for on-the-fly encryption, similar in its functionality to TrueCrypt. The goal of leet however is to be simpler and as user friendly as possible, making encryption and securing of information accessible to anybody, even those who don't necessarily have any prior knowledge of data securing, algorithms and encryption. However it's not targeted at this group of users only, part of the ambition of...
    Downloads: 0 This Week
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  • 10
    Modular toolkit for Data Processing MDP
    The Modular toolkit for Data Processing (MDP) is a Python data processing framework. From the user's perspective, MDP is a collection of supervised and unsupervised learning algorithms and other data processing units that can be combined into data processing sequences and more complex feed-forward network architectures. From the scientific developer's perspective, MDP is a modular framework, which can easily be expanded.
    Downloads: 3 This Week
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  • 11

    MarketSim

    A python based auction market simulator for agricultural trade

    The market assumes an environment in which farmers sell their produce through brokers and traders locate produce to buy through brokers. The major aim of the simulator is to experiment with various reputation mechanisms to manage bottlenecks and to model various adversarial scenarios. The market is aimed to simulate agricultural trade in developing countries. It is written in python and mysql database on Linux.
    Downloads: 0 This Week
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  • 12
    This project provides a set of Python tools for creating various kinds of neural networks, which can also be powered by genetic algorithms using grammatical evolution. MLP, backpropagation, recurrent, sparse, and skip-layer networks are supported.
    Downloads: 0 This Week
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  • 13
    This is a projct simulation code for my term report. It will be written in Python.
    Downloads: 0 This Week
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  • 14
    A univariate and multivariate analysis UI. This project is no longer under development. Please use as you wish.
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    Downloads: 6 This Week
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  • 15
    Design and develop Recommendation and Adaptive Prediction Engines to address eCommerce opportunities. Build a portfolio of engines by creating and porting algorithms from multiple disciplines to a usable form. Try to solve NetFlix and other challenges.
    Downloads: 0 This Week
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  • 16
    Automated computer program grading solutions designed for trainings on computer languages, data structures and algorithms. See http://openjudge.net for details.
    Downloads: 0 This Week
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  • 17
    SenseRank Sys: - builds the dictionaries (multidim matrices) of words’ values; - for the set utterance in certain language builds a figure in multidimensional space (in the matrix space) of values (visual schema), which is topological view of sense
    Downloads: 0 This Week
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  • 18
    Store your pieces of code and search it quickly
    Downloads: 0 This Week
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  • 19
    A neural net module written in python. The aim of the project is to provide a large set of neural network types accessed by an API that is easy to use and powerful.
    Downloads: 0 This Week
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  • 20
    eBarter froms trades from commitments. It measures economic values without the need of a common value standard; distributes fairly the gain produced between participants and gives the preference to trades where participants have the weakest requirements.
    Downloads: 0 This Week
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  • 21
    Institute of Technology, Blanchardstown Computer Science code by the class of 2007-2011 on course BN104. In this project we are open sourcing all of our project work to the public in the hopes it can be reused, built-upon, and used in education.
    Downloads: 0 This Week
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