Showing 19 open source projects for "network management"

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  • 1
    Haiku

    Haiku

    JAX-based neural network library

    ...It preserves Sonnet’s module-based programming model for state management while retaining access to JAX’s function transformations. Haiku can be expected to compose with other libraries and work well with the rest of JAX. Similar to Sonnet modules, Haiku modules are Python objects that hold references to their own parameters, other modules, and methods that apply functions on user inputs.
    Downloads: 4 This Week
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  • 2
    Awesome Fraud Detection Research Papers

    Awesome Fraud Detection Research Papers

    A curated list of data mining papers about fraud detection

    A curated list of data mining papers about fraud detection from several conferences.
    Downloads: 1 This Week
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  • 3
    DeepDetect

    DeepDetect

    Deep Learning API and Server in C++14 support for Caffe, PyTorch

    ...While the Open Source Deep Learning Server is the core element, with REST API, and multi-platform support that allows training & inference everywhere, the Deep Learning Platform allows higher level management for training neural network models and using them as if they were simple code snippets. Ready for applications of image tagging, object detection, segmentation, OCR, Audio, Video, Text classification, CSV for tabular data and time series. Neural network templates for the most effective architectures for GPU, CPU, and Embedded devices. ...
    Downloads: 16 This Week
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  • 4
    Synapse Machine Learning

    Synapse Machine Learning

    Simple and distributed Machine Learning

    SynapseML (previously MMLSpark) is an open source library to simplify the creation of scalable machine learning pipelines. SynapseML builds on Apache Spark and SparkML to enable new kinds of machine learning, analytics, and model deployment workflows. SynapseML adds many deep learning and data science tools to the Spark ecosystem, including seamless integration of Spark Machine Learning pipelines with the Open Neural Network Exchange (ONNX), LightGBM, The Cognitive Services, Vowpal Wabbit,...
    Downloads: 0 This Week
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  • Paessler - Monitor Your Whole Network in Minutes Icon
    Paessler - Monitor Your Whole Network in Minutes

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    Waiting weeks for a monitoring rollout isn't an option when infrastructure doesn't stop running. PRTG's auto-discovery scans your network and suggests from over 200 pre-configured sensor types, so you're watching servers, applications and devices within minutes, not after a multi-week deployment. Enterprise-strength monitoring, without the enterprise complexity. Start your free trial today.
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  • 5
    Lucid

    Lucid

    A collection of infrastructure and tools for research

    Lucid is a collection of infrastructure and tools for research in neural network interpretability. Lucid is research code, not production code. We provide no guarantee it will work for your use case. Lucid is maintained by volunteers who are unable to provide significant technical support. Start visualizing neural networks with no setup. The following notebooks run right from your browser, thanks to Collaboratory. It's a Jupyter notebook environment that requires no setup to use and runs...
    Downloads: 0 This Week
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  • 6
    CNN Explainer

    CNN Explainer

    Learning Convolutional Neural Networks with Interactive Visualization

    In machine learning, a classifier assigns a class label to a data point. For example, an image classifier produces a class label (e.g, bird, plane) for what objects exist within an image. A convolutional neural network, or CNN for short, is a type of classifier, which excels at solving this problem! A CNN is a neural network: an algorithm used to recognize patterns in data. Neural Networks in general are composed of a collection of neurons that are organized in layers, each with their own...
    Downloads: 0 This Week
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  • 7
    Forecasting Best Practices

    Forecasting Best Practices

    Time Series Forecasting Best Practices & Examples

    Time series forecasting is one of the most important topics in data science. Almost every business needs to predict the future in order to make better decisions and allocate resources more effectively. This repository provides examples and best practice guidelines for building forecasting solutions. The goal of this repository is to build a comprehensive set of tools and examples that leverage recent advances in forecasting algorithms to build solutions and operationalize them. Rather than...
    Downloads: 0 This Week
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  • 8
    uTensor

    uTensor

    TinyML AI inference library

    uTensor is an embedded machine learning inference framework designed to run neural network models on resource-constrained devices such as microcontrollers and Internet-of-Things hardware. The project focuses on enabling TinyML deployments by translating trained machine learning models into efficient C++ code that can execute directly on embedded systems. Instead of training models on-device, the framework uses an offline workflow that converts trained TensorFlow graphs into optimized...
    Downloads: 0 This Week
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  • 9
    Deep Learning with PyTorch

    Deep Learning with PyTorch

    Latest techniques in deep learning and representation learning

    This course concerns the latest techniques in deep learning and representation learning, focusing on supervised and unsupervised deep learning, embedding methods, metric learning, convolutional and recurrent nets, with applications to computer vision, natural language understanding, and speech recognition. The prerequisites include DS-GA 1001 Intro to Data Science or a graduate-level machine learning course. To be able to follow the exercises, you are going to need a laptop with Miniconda (a...
    Downloads: 0 This Week
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  • 10
    Image Quality Assessment

    Image Quality Assessment

    Convolutional Neural Networks to predict aesthetic quality of images

    Image Quality Assessment is an open-source deep learning project that implements neural models for predicting the aesthetic and technical quality of digital images. The repository provides an implementation inspired by the NIMA (Neural Image Assessment) research approach, which uses convolutional neural networks trained on human-annotated datasets to estimate image quality scores. The goal of the project is to automatically evaluate images based on perceived quality factors such as...
    Downloads: 0 This Week
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  • 11
    NiftyNet

    NiftyNet

    An open-source convolutional neural networks platform for research

    An open-source convolutional neural networks platform for medical image analysis and image-guided therapy. NiftyNet is a TensorFlow-based open-source convolutional neural networks (CNNs) platform for research in medical image analysis and image-guided therapy. NiftyNet’s modular structure is designed for sharing networks and pre-trained models. Using this modular structure you can get started with established pre-trained networks using built-in tools. Adapt existing networks to your imaging...
    Downloads: 0 This Week
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  • 12
    Docker Machine

    Docker Machine

    Machine management for a container-centric world

    Docker Machine is a tool that lets you install Docker Engine on virtual hosts, and manage the hosts with docker-machine commands. You can use Machine to create Docker hosts on your local Mac or Windows box, on your company network, in your data center, or on cloud providers like Azure, AWS, or DigitalOcean. Using docker-machine commands, you can start, inspect, stop, and restart a managed host, upgrade the Docker client and daemon, and configure a Docker client to talk to your host. Point...
    Downloads: 3 This Week
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  • 13

    Arabic Corpus

    Text categorization, arabic language processing, language modeling

    The Arabic Corpus {compiled by Dr. Mourad Abbas ( http://sites.google.com/site/mouradabbas9/corpora ) The corpus Khaleej-2004 contains 5690 documents. It is divided to 4 topics (categories). The corpus Watan-2004 contains 20291 documents organized in 6 topics (categories). Researchers who use these two corpora would mention the two main references: (1) For Watan-2004 corpus ---------------------- M. Abbas, K. Smaili, D. Berkani, (2011) Evaluation of Topic Identification Methods on...
    Downloads: 9 This Week
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  • 14
    LUMINOTH

    LUMINOTH

    Deep Learning toolkit for Computer Vision

    ...The toolkit provides command-line utilities for dataset management, training, and inference, making it easier to integrate into research workflows and production systems. Although the project is no longer actively maintained, it remains a useful educational and experimental platform for studying object detection pipelines and deep learning workflows.
    Downloads: 0 This Week
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  • 15
    DeepLearningProject

    DeepLearningProject

    An in-depth machine learning tutorial

    This tutorial tries to do what most Most Machine Learning tutorials available online do not. It is not a 30 minute tutorial that teaches you how to "Train your own neural network" or "Learn deep learning in under 30 minutes". It's a full pipeline which you would need to do if you actually work with machine learning - introducing you to all the parts, and all the implementation decisions and details that need to be made. The dataset is not one of the standard sets like MNIST or CIFAR, you...
    Downloads: 0 This Week
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  • 16
    Flamingo Project

    Flamingo Project

    Workflow Designer, Hive Editor, Pig Editor, File System Browser

    Flamingo is a open-source Big Data Platform that combine a Ajax Rich Web Interface + Workflow Engine + Workflow Designer + MapReduce + Hive Editor + Pig Editor. 1. Easy Tool for big data 2. Use comfortable in Hadoop EcoSystem projects 3. Based GPL V3 License Supporting Pig IDE, Hive IDE, HDFS Browser, Scheduler, Hadoop Job Monitoring, Workflow Engine, Workflow Designer, MapReduce.
    Downloads: 15 This Week
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  • 17

    AdPreqFr4SL

    Adaptive Prequential Learning Framework

    The AdPreqFr4SL learning framework for Bayesian Network Classifiers is designed to handle the cost / performance trade-off and cope with concept drift. Our strategy for incorporating new data is based on bias management and gradual adaptation. Starting with the simple Naive Bayes, we scale up the complexity by gradually updating attributes and structure. Since updating the structure is a costly task, we use new data to primarily adapt the parameters and only if this is really necessary, do we adapt the structure. ...
    Downloads: 0 This Week
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  • 18
    This project aims to develop a method to identify communities in a social network according to some point of view.
    Downloads: 0 This Week
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  • 19
    Neural Mesh
    Neural Mesh is a purely PHP, fast, easy Neural Network Manager, Administrator and Framework. It allows you to integrate Artificial Intelligence into your applications, quickly and easily, no matter what your experience.
    Downloads: 0 This Week
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