Search Results for "network" - Page 18
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Showing 27753 open source projects for "network"
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1
Dillo
Dillo, a multi-platform graphical web browser
...It is written in C and C++ using the FLTK (Fast Light Toolkit) GUI library. Its goals include enabling web access on old or constrained hardware, using slow or unreliable network connections, minimizing dependencies, and avoiding many of the complexities and overheads of modern full-featured browsers. It omits many modern features (notably JavaScript), instead focusing on rendering HTML (mostly older/standardized subsets), images, and some CSS, while keeping the codebase small. It is free/open source under GPL-3.0. -
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homebridge-samsung-tizen
Homebridge plugin for Samsung TV's with Tizen OS
...You can also use other methods by checking the Sponsor this project section from the right sidebar. This plugin was designed for Homebridge and will require you to set up a Homebridge server. Homebridge is a lightweight server you can run on your home network that emulates the iOS HomeKit API and allows you to control devices that are incompatible with HomeKit. -
3
macFuse
FUSE extends macOS by adding support for user space file systems
...As a developer, you can use the FUSE SDK to write numerous types of new file systems as regular user space programs. The content of these file systems can come from anywhere: from the local disk, from across the network, from memory, or any other combination of sources. Writing a file system using FUSE is orders of magnitude easier and quicker than the traditional approach of writing in-kernel file systems. Since FUSE file systems are regular applications (as opposed to kernel extensions), you have just as much flexibility and choice in programming tools, debuggers, and libraries as you have if you were developing standard macOS applications. -
4
Watermark-Removal
Machine learning image inpainting task that removes watermarks
...The system analyzes an image containing a watermark and attempts to reconstruct the underlying visual content so that the watermark is removed while preserving the original appearance of the image. The project uses neural network models inspired by research in contextual attention and gated convolution, which are methods commonly applied to image restoration tasks. Through these techniques, the model learns to identify regions of the image affected by the watermark and generate realistic replacements for the missing visual information. The repository contains code for preprocessing images, training the model, and running inference on images to automatically remove watermark artifacts. -
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5
uAgents
A fast and lightweight framework for creating decentralized agents
uAgents is a library developed by Fetch.ai that allows for creating autonomous AI agents in Python. With simple and expressive decorators, you can have an agent that performs various tasks on a schedule or takes action on various events. -
6
NNCF
Neural Network Compression Framework for enhanced OpenVINO
NNCF (Neural Network Compression Framework) is an optimization toolkit for deep learning models, designed to apply quantization, pruning, and other techniques to improve inference efficiency. -
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Microsoft365DSC
Manages, configures, and monitors Microsoft 365 tenant configurations
Automate your Change Management processes for your Microsoft 365 environments by maintaining a single declarative configuration file to manage all of your workloads. Microsoft365DSC allows you to take snapshots of the current configuration of any existing Microsoft 365 tenant. Microsoft365DSC is a configuration management tool for managing Microsoft 365 settings as code, enabling version control and automation. -
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Apache HertzBeat
Apache HertzBeat(incubating) is a real-time monitoring system
Apache HertzBeat (incubating) is an easy-to-use, open source, real-time monitoring system with an agentless, high-performance cluster, Prometheus-compatible, and offers powerful custom monitoring and status page building capabilities. Hertzbeat is an open-source monitoring and alerting platform for IT infrastructure, including servers, networks, and applications. -
9
Canmatrix
Converting Can (Controller Area Network) Database Formats
Canmatrix is a Python package to read and write several CAN (Controller Area Network) database formats. Canmatrix implements a "Python Can Matrix Object" which describes the can-communication and the needed objects (Board units, Frames, Signals, Values, ...) Canmatrix also includes two Tools (can convert and can compare) for converting and comparing CAN databases. -
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10
BitNet
BitNet: Scaling 1-bit Transformers for Large Language Models
BitNet is a machine learning research implementation that explores extremely low-precision neural network architectures designed to dramatically reduce the computational cost of large language models. The project implements the BitNet architecture described in research on scaling transformer models using extremely low-bit quantization techniques. In this approach, neural network weights are quantized to approximately one bit per parameter, allowing models to operate with far lower memory usage than traditional 16-bit or 32-bit neural networks. ... -
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Python Code Tutorials
The Python Code Tutorials
...Each tutorial typically includes complete Python code examples and explanations that demonstrate how to build real tools and applications step by step. Many tutorials focus on practical implementations such as building network scanners, web scraping tools, object detection systems, and automation utilities using Python libraries. The repository is organized into thematic directories that group tutorials by topic, allowing learners to navigate easily between areas such as ethical hacking, multimedia processing, or machine learning. -
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PyTorch-Tutorial-2nd
CV, NLP, LLM project applications, and advanced engineering deployment
PyTorch-Tutorial-2nd is an open-source educational repository that provides structured tutorials for learning deep learning with the PyTorch framework. The project serves as a practical companion to a second edition of a PyTorch learning guide and is designed to help learners understand neural network concepts through hands-on coding examples. The repository covers a wide range of topics including tensor operations, neural network construction, model training workflows, and optimization strategies. It also introduces practical machine learning techniques such as convolutional neural networks, recurrent networks, and other architectures commonly used in modern AI applications. ... -
13
Agents 2.0
An Open-source Framework for Data-centric Language Agents
Agents is an open-source framework designed to build and train autonomous language agents through a data-centric and learning-oriented architecture. The project introduces a concept known as agent symbolic learning, which treats an agent pipeline similarly to a neural network computational graph. In this framework, each node in the pipeline represents a step in the reasoning or action process, while prompts and tools act as adjustable parameters analogous to neural network weights. During training, the system performs a forward execution where the agent completes a task and records the trajectory of prompts, outputs, and tool usage. ... -
14
SSRFmap
Automatic SSRF fuzzer and exploitation tool
...It includes multiple exploitation “modules” for common SSRF-based attacks or pivoting techniques, such as DNS zone transfers, MySQL/Postgres command execution, Docker API info leaks, and network scans. Because SSRF often leads to lateral movement or internal network access, SSRFmap is especially useful for red-teamers and pentesters who want to explore chains rather than just the vulnerability surface. The repository also demonstrates a pragmatic mindset; rather than just “find SSRF”, it tries to “exploit SSRF” for impact, helping security testers build full end-to-end workflows. -
15
Tuba
Browse the Fediverse
...Stay connected to your favorite communities, family and friends with support for popular Fediverse platforms like Mastodon, GoToSocial, Akkoma & more. The Fediverse is a decentralized social network that consists of multiple interconnected platforms and communities, allowing users to communicate and share content across different networks and servers. It promotes user privacy and data ownership and offers an alternative to centralized social media platforms. -
16
NeuralOperators.jl
DeepONets, Neural Operators, Physics-Informed Neural Ops in Julia
...It learns an operator, which is a mapping between infinite-dimensional function spaces. It can be used to resolve partial differential equations (PDE). Instead of solving by finite element method, a PDE problem can be resolved by training a neural network to learn an operator mapping from infinite-dimensional space (u, t) to infinite-dimensional space f(u, t). Neural operator learns a continuous function between two continuous function spaces. The kernel can be trained on different geometry, which is learned from a graph. Fourier neural operator learns a neural operator with Dirichlet kernel to form a Fourier transformation. ... -
17
Secdev Scapy
Scapy: the Python-based interactive packet manipulation program
...Scapy can easily be used as an interactive shell to interact with the network. Scapy works without any external Python modules on Linux and BSD like operating systems. -
18
JetPackMvvm
A Jetpack combined with the MVVM rapid development framework
A Jetpack combined with the MVVM rapid development framework, based on the MVVM model to integrate the JetPack component library officially recommended by Google: LiveData, ViewModel, Lifecycle, and Navigation components use Kotlin language, add a lot of extension functions, simplify the code and add Retrofit network requests, coroutines, to help you Simplify various operations, allowing you to quickly develop projects. The sample format is the data format returned by the Android Api. If the errorCode is equal to 0, the request is successful, otherwise the request fails. From the developer's point of view, we mainly want to get the unpacking data-data, and we don't want to judge errorCode==0 every time. ... -
19
Opacus
Training PyTorch models with differential privacy
...Vectorized per-sample gradient computation that is 10x faster than micro batching. Supports most types of PyTorch models and can be used with minimal modification to the original neural network. Open source, modular API for differential privacy research. Everyone is welcome to contribute. ML practitioners will find this to be a gentle introduction to training a model with differential privacy as it requires minimal code changes. Differential Privacy researchers will find this easy to experiment and tinker with, allowing them to focus on what matters. -
20
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. -
21
PyG
Graph Neural Network Library for PyTorch
PyG (PyTorch Geometric) is a library built upon PyTorch to easily write and train Graph Neural Networks (GNNs) for a wide range of applications related to structured data. It consists of various methods for deep learning on graphs and other irregular structures, also known as geometric deep learning, from a variety of published papers. In addition, it consists of easy-to-use mini-batch loaders for operating on many small and single giant graphs, multi GPU-support, DataPipe support,... -
22
dockprom
Docker hosts and containers monitoring with Prometheus, Grafana, etc.
...CPU usage graph by mode (guest, idle, iowait, irq, nice, softirq, steal, system, user). Memory usage graph by distribution (used, free, buffers, cached). IO usage graph (read Bps, read Bps and IO time). Network usage graph by device (inbound Bps, Outbound Bps). -
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DeepCTR
Package of deep-learning based CTR models
DeepCTR is a Easy-to-use,Modular and Extendible package of deep-learning based CTR models along with lots of core components layers which can be used to easily build custom models. You can use any complex model with model.fit(), and model.predict(). Provide tf.keras.Model like interface for quick experiment. Provide tensorflow estimator interface for large scale data and distributed training. It is compatible with both tf 1.x and tf 2.x. With the great success of deep learning,DNN-based... -
24
Habitica
A habit tracker app which treats your goals like a Role Playing Game
...Habitica is a free habit building and productivity app that takes your real life as a game. With in-game rewards and punishments to motivate you and a strong social network to inspire you, Habitica can help you achieve your goals to be healthy, hardworking, and happy. Stay responsible by following and maintaining your Habits, Daily Tasks and To-Do Tasks with habitica's mobile apps and the website, both easy to use. Cross off tasks to level up your Avatar, and unlock in-game features like battle armor, mysterious pets, magical abilities, and even missions! ... -
25
Workerman
An asynchronous event driven PHP socket framework
...It has many high-performance components such as asynchronous Mysql, asynchronous Redis, asynchronous Http, MQTT Internet of Things client, and asynchronous message queue. Based on the high-performance Epoll event network library, a single machine can support millions of concurrent connections, with a long connection throughput of up to 36W/S. Objects such as PHP database can be resident in memory, reducing analysis and compilation and network overhead.
