Search Results for "network tools" - Page 2
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Showing 57 open source projects for "network tools"
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Gonum
Set of numeric libraries for the Go programming language
...Gonum is a set of packages designed to make writing numerical and scientific algorithms productive, performant, and scalable. Gonum contains libraries for matrices and linear algebra; statistics, probability distributions, and sampling; tools for function differentiation, integration, and optimization; network creation and analysis; and more. We encourage you to get started with Go and Gonum if you are tired of sluggish performance, and fighting C and vectorization, and also if you are struggling with managing programs as they grow larger. Get Gonum if you want code to be fully transparent, and want the ability to read the source code you use. ... -
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Horde
Horde is a distributed Supervisor and Registry
...With Horde.Registry you register processes globally and look them up anywhere, while Horde.DynamicSupervisor starts and migrates children across nodes, rebalancing as capacity or health changes. Because everything runs under OTP supervision, failures are isolated and recoveries are automatic, even during network partitions or rolling deploys. It integrates naturally with common clustering tools and plays well with PubSub, job systems, and presence tracking. The result is predictable, configuration-driven distribution that removes a lot of custom glue typically needed for multi-node Elixir systems. -
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Infosec Reference
An Information Security Reference That Doesn't Suck
Infosec Reference is a curated knowledge base and resource repository for information security practitioners. It aggregates cheat sheets, tooling guides, protocol deep dives, incident response playbooks, and threat actor profiles—all organized under accessible categories (network, web, host, cryptography, auditing). The repo is built as a living wiki of sorts: practitioners contribute updates, expand sections, or refine explanations as the threat landscape evolves. Because security spans... -
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freefq
Wall climb, free wall climb, free science internet access
freefq is a community-driven open-source project that provides curated lists of free and publicly available proxy server configurations and endpoints to help users bypass network restrictions and improve internet access. The repository aggregates working proxy server addresses (such as Shadowsocks, V2Ray, Trojan, and other protocols) shared by contributors, enabling users to configure their client tools quickly without having to search fragmented sources. It aims to maintain up-to-date entries through frequent commits and community reporting, helping remove outdated or nonfunctional proxies while promoting lists that users have verified as usable. ... -
Go from Code to Production URL in SecondsSkip the Kubernetes configs. Cloud Run handles HTTPS, scaling, and infrastructure automatically. Two million requests free per month.
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Neural Tangents
Fast and Easy Infinite Neural Networks in Python
Neural Tangents is a high-level neural network API for specifying complex, hierarchical models at both finite and infinite width, built in Python on top of JAX and XLA. It lets researchers define architectures from familiar building blocks—convolutions, pooling, residual connections, and nonlinearities—and obtain not only the finite network but also the corresponding Gaussian Process (GP) kernel of its infinite-width limit. With a single specification, you can compute NNGP and NTK kernels,... -
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Penetration Testing Tools
A collection of more than 170+ tools, scripts, cheatsheets
Penetration-Testing-Tools is a curated collection of tools, scripts, cheatsheets and reference materials assembled to help security researchers, red-teamers, and students perform hands-on penetration testing across multiple domains. The repository groups resources by discipline — reconnaissance, web application testing, network exploitation, privilege escalation, post-exploitation and reporting — so users can quickly find relevant utilities and walkthroughs. -
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Darknet
Convolutional Neural Networks
Darknet is an open source neural network framework written in C and CUDA, developed by Joseph Redmon. It is best known as the original implementation of the YOLO (You Only Look Once) real-time object detection system. Darknet is lightweight, fast, and easy to compile, making it suitable for research and production use. The repository provides pre-trained models, configuration files, and tools for training custom object detection models. -
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SVoice (Speech Voice Separation)
We provide a PyTorch implementation of the paper Voice Separation
SVoice is a PyTorch-based implementation of Facebook Research’s study on speaker voice separation as described in the paper “Voice Separation with an Unknown Number of Multiple Speakers.” This project presents a deep learning framework capable of separating mixed audio sequences where several people speak simultaneously, without prior knowledge of how many speakers are present. The model employs gated neural networks with recurrent processing blocks that disentangle voices over multiple... -
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QB64
BASIC for the modern era
QB64 is a modern self-hosting BASIC compiler that brings classic QBasic/QuickBASIC programs into the modern era. It enables legacy code to run on today’s operating systems with minimal modifications, while also introducing new commands and libraries for multimedia, networking, and 64-bit computing. QB64 compiles to C++ and includes a built-in IDE, making it accessible for beginners, hobbyists, and retro programming enthusiasts. It aims to preserve the ease and nostalgia of BASIC while... -
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YOLOR
implementation of paper - You Only Learn One Representation
...YOLOR includes model configurations, training code, evaluation scripts, inference tools, and pretrained weights. Its central contribution is the use of implicit knowledge to improve network performance without treating every task as fully separate. It is useful for computer vision researchers and developers studying YOLO-style detectors, representation learning, and high-performance detection systems. -
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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. -
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Hack-Tools
Hack tools
hack-tools is a collection of various hacking tools and utilities. It serves as a comprehensive toolkit for penetration testers and cybersecurity enthusiasts, encompassing a wide range of functionalities. -
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peertalk
iOS and Mac Cocoa library for communicating over USB
...The project is aimed at scenarios where you want a reliable, direct link between a Mac app and an iOS app without relying on Wi-Fi discovery, manual hostnames, or network exposure. A key motivation is that a USB link is inherently constrained to the devices at each end of the cable, which can make the communication model feel more contained and straightforward for certain tooling or companion-app setups. Typical use cases include developer tools, companion displays, device-to-desktop instrumentation, or any workflow where an iOS device acts as a peripheral to a desktop app. ... -
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OHHTTPStubs
Stub your network requests easily!
...Instead of writing the content of the stubs you want to use manually, you can use tools like SWHttpTrafficRecorder to record network requests into files. This way you can later use those files as stub responses. OHHTTPStubs is split into subspecs so that when using Cocoapods, you can get only what you need, no more, no less. OHHTTPStubs supports Swift 2.2 (Xcode 7), Swift 2.3 (Xcode 8), Swift 3.0 (Xcode 8+) and Swift 3.1 (Xcode 8.3+). -
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fastNLP
fastNLP: A Modularized and Extensible NLP Framework
...A unified Tabular data container simplifies the data preprocessing process. Built-in Loader and Pipe for multiple datasets, eliminating the need for preprocessing code. Various convenient NLP tools, such as Embedding loading (including ELMo and BERT), intermediate data cache, etc.. Provide a variety of neural network components and recurrence models (covering tasks such as Chinese word segmentation, named entity recognition, syntactic analysis, text classification, text matching, metaphor resolution, summarization, etc.). Trainer provides a variety of built-in Callback functions to facilitate experiment recording, exception capture, etc. ... -
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The Neural Process Family
This repository contains notebook implementations
Neural Processes (NPs) is a collection of interactive Jupyter/Colab notebook implementations developed by Google DeepMind, showcasing three foundational probabilistic machine learning models: Conditional Neural Processes (CNPs), Neural Processes (NPs), and Attentive Neural Processes (ANPs). These models combine the strengths of neural networks and stochastic processes, allowing for flexible function approximation with uncertainty estimation. They can learn distributions over functions from... -
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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 foundational ideas from DeepMind’s paper “Relational Inductive Biases, Deep Learning, and Graph Networks”, offering tools to explore relational reasoning and message-passing neural networks. ... -
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Mars
A cross-platform network component developed by WeChat
Mars is an open source, cross-platform infrastructure component and official terminal basic component of WeChat. It consists of four main parts: Comm, which contains a basic library, including basic tools like sockets, threads, alarm, message queues, and coroutines; Xlog, which provides high-performance, high-availability, security, and fault-tolerant log functions; SDT which is the network diagnosis module; and STN or signaling transmission network module, the major component of Mars responsible for the small data signaling channel between the terminal and the server. ... -
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Video Nonlocal Net
Non-local Neural Networks for Video Classification
video-nonlocal-net implements Non-local Neural Networks for video understanding, adding long-range dependency modeling to 2D/3D ConvNet backbones. Non-local blocks compute attention-like responses across all positions in space-time, allowing a feature at one frame and location to aggregate information from distant frames and regions. This formulation improves action recognition and spatiotemporal reasoning, especially for classes requiring context beyond short temporal windows. The repo... -
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EventMachine
EventMachine, fast, simple event-processing library for Ruby programs
EventMachine is an event-driven I/O and lightweight concurrency library for Ruby. It provides event-driven I/O using the Reactor pattern, much like JBoss Netty, Apache MINA, Python's Twisted, Node.js, libevent and libev. Extremely high scalability, performance and stability for the most demanding production environments. An API that eliminates the complexities of high-performance threaded network programming, allowing engineers to concentrate on their application logic. This unique... -
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PyTorch Book
PyTorch tutorials and fun projects including neural talk
This is the corresponding code for the book "The Deep Learning Framework PyTorch: Getting Started and Practical", but it can also be used as a standalone PyTorch Getting Started Guide and Tutorial. The current version of the code is based on pytorch 1.0.1, if you want to use an older version please git checkout v0.4or git checkout v0.3. Legacy code has better python2/python3 compatibility, CPU/GPU compatibility test. The new version of the code has not been fully tested, it has been tested... -
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cnn-benchmarks
Benchmarks for popular CNN models
The cnn-benchmarks project is a collection of benchmarking scripts designed to evaluate the performance of convolutional neural networks across different hardware and configurations. It provides standardized implementations of popular CNN architectures, enabling developers to measure training speed, memory usage, and computational efficiency. The project focuses on reproducibility, allowing consistent comparisons between models and environments. It is particularly useful for testing GPUs and... -
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Swift AI
The Swift machine learning library
Swift AI is a high-performance deep learning library written entirely in Swift. We currently offer support for all Apple platforms, with Linux support coming soon. Swift AI includes a collection of common tools used for artificial intelligence and scientific applications. A flexible, fully-connected neural network with support for deep learning. Optimized specifically for Apple hardware, using advanced parallel processing techniques. We've created some example projects to demonstrate the usage of Swift AI. Each resides in their own repository and can be built with little or no configuration. ... -
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PrettyTensor
Pretty Tensor: Fluent Networks in TensorFlow
Pretty Tensor is a high-level API built on top of TensorFlow that simplifies the process of creating and managing deep learning models. It wraps TensorFlow tensors in a chainable object syntax, allowing developers to build multi-layer neural networks with concise and readable code. Pretty Tensor preserves full compatibility with TensorFlow’s core functionality while providing syntactic sugar for defining complex architectures such as convolutional and recurrent networks. The library’s design... -
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ffnet is a fast and easy-to-use feed-forward neural network training solution for python. Many nice features are implemented: arbitrary network connectivity, automatic data normalization, very efficient training tools, network export to fortran code. Now ffnet has also a GUI called ffnetui.
