Showing 406 open source projects for "network development platforms"

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  • 1
    Frontend Regression Validator (FRED)

    Frontend Regression Validator (FRED)

    Visual regression tool used to compare baseline and updated instances

    Visual regression tool used to compare baseline and updated instances of a website in a deployment pipeline. FRED is an opensource visual regression tool used to compare two instances of a website. FRED is responsible for automatic visual regression testing, with the purpose of ensuring that functionality is not broken by comparing a current(baseline) and an updated version of a website. The visual analysis computes the Normalized Mean Squared error and the Structural Similarity Index on the...
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  • 2
    PerfKit Benchmarker

    PerfKit Benchmarker

    PerfKit Benchmarker (PKB) contains a set of benchmarks

    PerfKitBenchmarker is an open-source benchmarking framework designed to measure and compare the performance of cloud infrastructure across multiple providers in a consistent and reproducible way. It allows users to evaluate metrics such as latency, throughput, provisioning time, and system performance using a standardized set of benchmarks. The tool supports a wide range of environments, including major cloud platforms, Kubernetes clusters, and even local hardware, making it highly versatile...
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  • 3
    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...
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  • 4
    AdaNet

    AdaNet

    Fast and flexible AutoML with learning guarantees

    AdaNet is a TensorFlow framework for fast and flexible AutoML with learning guarantees. AdaNet is a lightweight TensorFlow-based framework for automatically learning high-quality models with minimal expert intervention. AdaNet builds on recent AutoML efforts to be fast and flexible while providing learning guarantees. Importantly, AdaNet provides a general framework for not only learning a neural network architecture but also for learning to the ensemble to obtain even better models. At each...
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  • 5
    Unified Sessions Manager

    Unified Sessions Manager

    Pioneering Private and Public Cloud Management since 2008

    The UnifiedSessionsManager supports the integrated management of user sessions within Private-Clouds, comprising heterogeneous IT landscapes of various physical and virtual machines, hypervisor management, and virtual user sessions with remote desktops. Extracted documents see https://sourceforge.net/projects/ctys-doc.
    Downloads: 3 This Week
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  • 6
    Clay Golem

    Clay Golem

    Golem is creating a global market for computing power

    The Golem Network fosters a global group of creators building ambitious software solutions that will shape the technological landscape of future generations by accessing computing resources across the platform. Golem Network is an accessible, reliable, open access and censorship-resistant protocol, democratizing access to digital resources and connecting users through a flexible, open-source platform. With Golem Network, users can connect with ease and pay each other for sharing their unused...
    Downloads: 2 This Week
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  • 7
    stage0

    stage0

    A set of minimal dependency bootstrap binaries

    This is a set of manually created hex programs in a Cthulhu Path to madness fashion. Which only have the goal of creating a bootstrapping path to a C compiler capable of compiling GCC, with only the explicit requirement of a single 1 KByte binary or less. Additionally, all code must be able to be understood by 70% of the population of programmers. If the code can not be understood by that volume, it needs to be altered until it satisfies the above requirement.
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  • 8
    CrypTen

    CrypTen

    A framework for Privacy Preserving Machine Learning

    ...Designed to make secure computation accessible to machine learning practitioners, CrypTen introduces a CrypTensor object that behaves like a regular PyTorch tensor, allowing users to seamlessly apply automatic differentiation and neural network operations. Its design mirrors PyTorch’s modular and library-based structure, enabling flexible experimentation, debugging, and model development. The framework supports both encryption and decryption of tensors and operations such as addition and multiplication over encrypted values. Although not yet production-ready, CrypTen focuses on advancing real-world secure ML applications, such as training and inference over private datasets, without exposing sensitive data.
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  • 9
    Graph Nets library

    Graph Nets library

    Build Graph Nets in Tensorflow

    Graph Nets, developed by Google DeepMind, is a Python library designed for constructing and training graph neural networks (GNNs) using TensorFlow and Sonnet. It provides a high-level, flexible framework for building neural architectures that operate directly on graph-structured data. A graph network takes graphs as inputs, consisting of edges, nodes, and global attributes, and produces updated graphs with modified feature representations at each level. This library implements the...
    Downloads: 2 This Week
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    Custom VMs From 1 to 96 vCPUs With 99.95% Uptime

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  • 10
    This system is designed to synchronize objects over network using a 1 server : n clients topology. In contrast to Object Replication system used in Zoidcom or RakNet this solution is developed to be very scalable using multiple threads/cpus=> MMO ready.
    Downloads: 0 This Week
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  • 11
    Ouroboros

    Ouroboros

    Automatically update running docker containers

    Ouroboros will monitor (all or specified) running docker containers and update them to the (latest or tagged) available image in the remote registry. The updated container uses the same tag and parameters that were used when the container was first created such as volume/bind mounts, docker network connections, environment variables, restart policies, entrypoints, commands, etc. Push your image to your registry and simply wait your defined interval for ouroboros to find the new image and redeploy your container autonomously. Notify you via many platforms courtesy of Apprise. Serve metrics for trend monitoring (Currently: Prometheus/Influxdb) Per-command and scenario examples can be found in the wiki.
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  • 12
    Python basic brick interface
    This project is a set of usefull classes to manage data from de database to the user interface. Based on a dictionary who match the DB table, the panel will be created.
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  • 13

    Python DB-API 2.0 module for ADO

    Use Microsoft ADO to read/write most data bases.

    Python module that makes it easy to use Microsoft ADO for connecting with databases and other data sources. For CPython users, this module is included as part of pywin32 (https://github.com/mhammond/pywin32), and continued support will take place there. This fork will be maintained for Iron Python users. * Documentation at http://adodbapi.sourceforge.net/quick_reference.pdf or quick_reference.odb in the .zip
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  • 14
    PyTorch Natural Language Processing

    PyTorch Natural Language Processing

    Basic Utilities for PyTorch Natural Language Processing (NLP)

    PyTorch-NLP is a library for Natural Language Processing (NLP) in Python. It’s built with the very latest research in mind, and was designed from day one to support rapid prototyping. PyTorch-NLP comes with pre-trained embeddings, samplers, dataset loaders, metrics, neural network modules and text encoders. It’s open-source software, released under the BSD3 license. With your batch in hand, you can use PyTorch to develop and train your model using gradient descent. For example, check out...
    Downloads: 2 This Week
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  • 15
    setuptestx

    setuptestx

    Support of unit tests on multiple platforms and implementations.

    The 'setuptestx' supports a common call interface for the major implementations and releases of Python on various operating systems and their variants of distributions. The current provided implementations are: - CPython, IPython, PyPY : Python2.7, and Python3.5+ - IronPython, Jython : Python2.7 For the OS see *Tested Platforms* in the manuals.
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  • 16
    platformids

    platformids

    OS and Distribution Release Enumeration

    The ‘platformids‘ package provides the categorization and enumeration of OS platforms and distributions. This enables the development of portable generic code for arbitrary platforms in IT and IoT landscapes consisting of heterogeneous physical and virtual runtime environments. The introduced hierarchical bitmask vectors enable for fast and efficient platform specific code and data selection for OS and distributions with routines for specific platform releases. ...
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  • 17
    pysourceinfo

    pysourceinfo

    RTTI for Python Source and Binary Files

    The 'pysourceinfo' package provides source information on Python runtime objects based on 'inspect', 'sys', 'os', and 'imp'. The covered objects include packages, modules, functions, methods, scripts, and classes by two views: - File System View - packages, modules, and linenumbers - based on files and paths - Runtime Object View - callables, classes, and containers - based on in-memory RTTI / introspection The supported platforms are: - Linux, BSD, Unix, OS-X, Cygwin, and...
    Downloads: 2 This Week
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  • 18
    pythonids

    pythonids

    Enumeration of Python implementations and releases

    The ‘pythonids‘ package provides the enumeration of Python syntaxes and the categorization of Python implementations. This enables the development of fast and easy portable generic code for arbitrary platforms in IT and IoT landscapes consisting of heterogeneous physical and virtual runtime environments. The current supported syntaxes are Python2.7+ and Python3 for the Python implementations: CPython IPython (based on CPython) IronPython Jython PyPy
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  • 19
    I3D models trained on Kinetics

    I3D models trained on Kinetics

    Convolutional neural network model for video classification

    Kinetics-I3D, developed by Google DeepMind, provides trained models and implementation code for the Inflated 3D ConvNet (I3D) architecture introduced in the paper “Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset” (CVPR 2017). The I3D model extends the 2D convolutional structure of Inception-v1 into 3D, allowing it to capture spatial and temporal information from videos for action recognition. This repository includes pretrained I3D models on the Kinetics dataset, with...
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  • 20
    WALKOFF

    WALKOFF

    A flexible, easy to use, automation framework

    Faster, smarter, cheaper operations through automation. WALKOFF puts the tools in your hands to easily automate the tedious repetitive tasks dragging your operations down. Act smarter with WALKOFF by automatically gathering data, analyzing data, or visualizing data customized to your requirements. Act faster with WALKOFF by integrating the capabilities you already own to dynamically respond on your terms to your fast-moving environment. Drag and drop workflow editor. Sharable apps and...
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  • 21
    Nebula worker

    Nebula worker

    The worker node manager container which manages nebula nodes

    Nebula is a open source distributed Docker orchestrator designed for massive scales (tens of thousands of servers/worker devices), unlike Mesos/Swarm/Kubernetes it has the ability to have workers distributed on high latency connections (such as the internet) yet have the pods(containers) be managed centrally with changes taking affect (almost) immediately, this makes Nebula ideal for managing a vast cluster of servers\devices across the globe, some example use cases are IoT devices,...
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  • 22
    Olex2 is visualisation software for small-molecule crystallography developed at Durham University/EPSRC. It provides comprehensive tools for crystallographic model manipulation for the end user and an extensible development framework for programmers. The project has been supported by Olexsys Ltd since 2010.
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  • 23
    The Google Cloud Developer's Cheat Sheet

    The Google Cloud Developer's Cheat Sheet

    Cheat sheet for Google Cloud developers

    Every product in the Google Cloud family described in <=4 words (with liberal use of hyphens and slashes) by the Google Developer Relations Team. This list only includes products that are publicly available. There are several products in pre-release/private-alpha that will not be included until they go public beta or GA. Many of these products have a free tier. There is also a free trial that will enable you try almost everything. API platforms and ecosystems, developer and management tools,...
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  • 24
    captcha_break

    captcha_break

    Identification codes

    This project will use Keras to build a deep convolutional neural network to identify the captcha verification code. It is recommended to use a graphics card to run the project. The following visualization codes are jupyter notebookall done in . If you want to write a python script, you can run it normally with a little modification. Of course, you can also remove these visualization codes. captcha is a library written in python to generate verification codes. It supports image verification...
    Downloads: 1 This Week
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  • 25
    GRAMD® Personal Signature

    GRAMD® Personal Signature

    Digital Signature for PDF documents in Spanish

    Eng: Digital Signature with x.509 certificates and smartcards for PDFand PAdES format documents in Spanish for Windows OS (8 and 10). Esp: Firma Digital de documents electrónicos PDF en formato PAdES con certificados digitales X.509 y tokens criptográficos en español.
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