Showing 7 open source projects for "abrviewer-net"

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  • Custom VMs From 1 to 96 vCPUs With 99.95% Uptime Icon
    Custom VMs From 1 to 96 vCPUs With 99.95% Uptime

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    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.

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  • 1
    NeuralProphet

    NeuralProphet

    A simple forecasting package

    NeuralProphet bridges the gap between traditional time-series models and deep learning methods. It's based on PyTorch and can be installed using pip. A Neural Network based Time-Series model, inspired by Facebook Prophet and AR-Net, built on PyTorch. You can find the datasets used in the tutorials, including data preprocessing examples, in our neuralprophet-data repository. The documentation page may not we entirely up to date. Docstrings should be reliable, please refer to those when in doubt. We are working on an improved documentation. We appreciate any help to improve and update the docs. ...
    Downloads: 0 This Week
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  • 2
    DeepCTR-Torch

    DeepCTR-Torch

    Easy-to-use,Modular and Extendible package of deep-learning models

    ...Factorization-Machine and it’s variants are widely used to learn the low-order feature interaction. High-order Extractor learns feature combination through complex neural network functions like MLP, Cross Net, etc.
    Downloads: 0 This Week
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  • 3
    Adaptive Intelligence

    Adaptive Intelligence

    Adaptive Intelligence also known as "Artificial General Intelligence"

    Adaptive Intelligence is the implementation of neural science, forensic psychology , behavioral science with machine-learning and artificial intelligence to provide advanced automated software platforms with the ability to adjust and thrive in dynamic environments by combining cognitive flexibility, emotional regulation, resilience, and practical problem-solving skills.
    Downloads: 1 This Week
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  • 4
    MMDeploy

    MMDeploy

    OpenMMLab Model Deployment Framework

    ...Models can be exported and run in several backends, and more will be compatible. All kinds of modules in the SDK can be extended, such as Transform for image processing, Net for Neural Network inference, Module for postprocessing and so on. Install and build your target backend. ONNX Runtime is a cross-platform inference and training accelerator compatible with many popular ML/DNN frameworks. Please read getting_started for the basic usage of MMDeploy.
    Downloads: 0 This Week
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  • Compliant and Reliable File Transfers Backed by Top Security Certifications Icon
    Compliant and Reliable File Transfers Backed by Top Security Certifications

    Cerberus FTP Server delivers SOC 2 Type II certified security and FIPS 140-2 validated encryption.

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  • 5
    fastMRI

    fastMRI

    A large open dataset + tools to speed up MRI scans using ML

    ...The repository provides an open-source PyTorch framework with data loaders, subsampling utilities, reconstruction models, and evaluation metrics, supporting both research reproducibility and practical experimentation. It includes reference implementations for key MRI reconstruction architectures such as U-Net and Variational Networks (VarNet), along with example scripts for model training and evaluation using the PyTorch Lightning framework. The project also releases several fully anonymized public MRI datasets, including knee, brain, and prostate scans.
    Downloads: 3 This Week
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  • 6
    Neural Network signal recognition rtlsdr

    Neural Network signal recognition rtlsdr

    Deep learning signal classification (recognition) using rtl-sdr dongle

    WARNING: Outdated version here. Everything has been moved to github: https://github.com/randaller/cnn-rtlsdr
    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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