Search Results for "network data speed" - Page 4
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Showing 183 open source projects for "network data speed"
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Atera all-in-one platform IT management software with AI agentsAtera’s AI agents don’t just assist, they act. From detection to resolution, they handle incidents and requests instantly, taking your IT management from automated to autonomous.
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AestheticsPro Medical Spa SoftwareAestheticsPro is the most complete Aesthetics Software on the market today. HIPAA Cloud Compliant with electronic charting, integrated POS, targeted marketing and results driven reporting; AestheticsPro delivers the tools you need to manage your medical spa business. It is our mission To Provide an All-in-One Cutting Edge Software to the Aesthetics Industry.
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Neural Network Intelligence
AutoML toolkit for automate machine learning lifecycle
Neural Network Intelligence is an open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning. NNI (Neural Network Intelligence) is a lightweight but powerful toolkit to help users automate feature engineering, neural architecture search, hyperparameter tuning and model compression. The tool manages automated machine learning (AutoML) experiments, dispatches and runs experiments'... -
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multiOTP open source
PHP strong authentication library, web interface & CLI, OATH certified
multiOTP is a PHP class, a powerful command line utility and a web interface developed by SysCo systèmes de communication sa in order to provide a completely free and easy operating system independent server side implementation for strong two factors authentication solution. multiOTP supports hardware and software tokens with different One-Time Password algorithms like OATH/HOTP, OATH/TOTP and mOTP (Mobile-OTP). QRcode generation is also embedded in order to support provisioning of Google... -
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ALEPH-w
Data structures and Algorithms library
...Dynamic linear hash tables are implemented too. The main algorithms on graphs are implemented in an easy way and with good performance features. Network Flow (maximum and min cost), cut points, topological sort, spanning trees, min paths. etc. The graphs are generic in the sense that they can contain data independent of the algorithm. Several containers of the C++ STL library are implemented with Aleph-w. Their performance is better than GNU implementation -
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libfc4c
Fast containers for C language
C dynamic containers are missing in the standard, so almost every single project in C uses different implementations. This library is yet another implementation of few basic containers, optimized for speed. A simplified interface to libarchive allows to save the containers in a compressed form. All the containers are 32bit. This greatly improves the performance (up to ~32%) and reduces the memory consumption (up to 41%) on 64bit systems. All the containers are pre-allocating buffers to... -
Skillfully - The future of skills based hiringSkillfully transforms hiring through AI-powered skill simulations that show you how candidates actually perform before you hire them. Our platform helps companies cut through AI-generated resumes and rehearsed interviews by validating real capabilities in action. Through dynamic job specific simulations and skill-based assessments, companies like Bloomberg and McKinsey have cut screening time by 50% while dramatically improving hire quality.
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eCxx
A C++ library for AVR and NodeMCU
NOTE: This project is marked with 'Status: Abandoned' on SourceForge because not enough time can be dedicated to this project. However it may still get sporadic commits to the repository. eCxx is a library for AVR and NodeMCU tailored for micro LED displays and lighting effects. eCxx is utilizing Makefile build system. Java and Python based applications/tools are also included to ease the development and debugging process using the host PC. On one side, eCxx supports the original... -
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JavaScript & Node.js Testing
Comprehensive and exhaustive JavaScript & Node.js testing
This project compiles practical advice for testing JavaScript applications across the stack, emphasizing clarity, speed, and reliability over dogma. It distinguishes between different kinds of tests—unit, integration, end-to-end—and shows when each is appropriate given time and risk constraints. The guide focuses on removing flakiness by isolating side effects, controlling randomness, and stabilizing async code paths. It also demonstrates test design techniques like arranging test data, using expressive assertions, and structuring test suites for readability and discoverability. ... -
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fastMRI
A large open dataset + tools to speed up MRI scans using ML
fastMRI is a large-scale collaborative research project by Facebook AI Research (FAIR) and NYU Langone Health that explores how deep learning can accelerate magnetic resonance imaging (MRI) acquisition without compromising image quality. By enabling reconstruction of high-fidelity MR images from significantly fewer measurements, fastMRI aims to make MRI scanning faster, cheaper, and more accessible in clinical settings. The repository provides an open-source PyTorch framework with data... -
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Neural Network Visualization
Project for processing neural networks and rendering to gain insights
nn_vis is a minimalist visualization tool for neural networks written in Python using OpenGL and Pygame. It provides an interactive, graphical representation of how data flows through neural network layers, offering a unique educational experience for those new to deep learning or looking to explain it visually. By animating input, weights, activations, and outputs, the tool demystifies neural network operations and helps users intuitively grasp complex concepts. Its lightweight codebase is great for customization and teaching purposes. -
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Alpa
Training and serving large-scale neural networks
Alpa is a system for training and serving large-scale neural networks. Scaling neural networks to hundreds of billions of parameters has enabled dramatic breakthroughs such as GPT-3, but training and serving these large-scale neural networks require complicated distributed system techniques. Alpa aims to automate large-scale distributed training and serving with just a few lines of code. -
Collect! is a highly configurable debt collection softwareThe flexible & scalable debt collection software built to automate your workflow. From startup to enterprise, we have the solution for you.
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ml-surveys
Survey papers summarizing advances in deep learning, NLP, CV, graphs
...Instead of diving into code or experiments, this repo gathers authoritative survey and review articles, summarizing the state-of-the-art, trends, challenges, and directions within each subdomain. For someone trying to get up to speed with a new ML subfield — say graph neural networks or meta-learning — ml-surveys offers a curated reading list of foundational and recent works, helping map the landscape quickly. It is particularly useful for researchers, data scientists, or engineers who want conceptual clarity about where a field stands, what problems remain, and what techniques are most established. -
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Darknet YOLO
Real-Time Object Detection for Windows and Linux
This is YOLO-v3 and v2 for Windows and Linux. YOLO (You only look once) is a state-of-the-art, real-time object detection system of Darknet, an open source neural network framework in C. YOLO is extremely fast and accurate. It uses a single neural network to divide a full image into regions, and then predicts bounding boxes and probabilities for each region. This project is a fork of the original Darknet project. -
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Jraph
A Graph Neural Network Library in Jax
Jraph (pronounced “giraffe”) is a lightweight JAX library developed by Google DeepMind for building and experimenting with graph neural networks (GNNs). It provides an efficient and flexible framework for representing, manipulating, and training models on graph-structured data. The core of Jraph is the GraphsTuple data structure, which enables users to define graphs with arbitrary node, edge, and global attributes, and to batch variable-sized graphs efficiently for JAX’s just-in-time... -
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Google IPs
Public IP address ranges associated with Google infrastructure
Google-IPs aggregates public IP address ranges that are associated with Google’s infrastructure, collecting them in machine-readable formats useful for routing and firewall rules. The list is helpful for administrators who need to whitelist Google endpoints, analyze traffic, or tune proxies and CDN configurations. By centralizing ranges that are otherwise spread across announcements and registries, it saves time and reduces misconfiguration risk. The repository typically includes CIDR blocks... -
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CityHash
Automatically exported from Google code CityHash
...CityHash offers multiple hash sizes—32-bit, 64-bit, 128-bit, and 256-bit variants—with the CRC-based versions leveraging hardware acceleration on CPUs that support SSE4.2 CRC32 instructions. The library emphasizes hashing performance and uniformity rather than cryptographic security, making it ideal for use in data structures like hash tables and distributed systems requiring rapid key lookups. CityHash has been rigorously tested using tools like SMHasher to ensure high-quality mixing and collision resistance across a wide range of inputs. Its speed and portability have made it a popular choice for developers needing dependable, lightweight hash functions. -
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D-List
An extensive list subsystem, written in C
...It was written primarily for accuracy and speed, and provides extensive debugging support for easy code development. -
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Fairseq
Facebook AI Research Sequence-to-Sequence Toolkit written in Python
Fairseq(-py) is a sequence modeling toolkit that allows researchers and developers to train custom models for translation, summarization, language modeling and other text generation tasks. We provide reference implementations of various sequence modeling papers. Recent work by Microsoft and Google has shown that data parallel training can be made significantly more efficient by sharding the model parameters and optimizer state across data parallel workers. These ideas are encapsulated in the new FullyShardedDataParallel (FSDP) wrapper provided by fairscale. Fairseq can be extended through user-supplied plug-ins. Models define the neural network architecture and encapsulate all of the learnable parameters. ... -
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NeuroNet
Neural network program. Creates and trains neural networks, shows data
Neural network program. Creates and trains neural networks, shows data. -
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NestProfessor Programmer Edition
Nesting SDK, Library
This is a SDK which can nest/layout the part/geometry/polygon on the material or sheet intelligently, you can get the best utilization of the materials, this SDK also support read/write DXF/DWG files and part-in-part nesting. New nesting lagorithm is implenmented, more good to support true shape part or material. -
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BizCharts
Powerful data visualization library based on G2 and React
BizCharts is Alibaba's general charting component library, dedicated to creating efficient, professional and convenient data visualization solutions in the middle and backend of enterprises. Based on the React charting library packaged by G2 and G2Plot, it has experienced three years of baptism in Alibaba's complex business scenarios. In terms of convenience, ease of use, and richness, it satisfies the business implementation of conventional charts and highly customized charts. After years... -
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TensorFlow Examples
TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
TensorFlow Examples is a comprehensive repository of example implementations, tutorials, and reference code intended to help newcomers and intermediate learners dive into TensorFlow quickly. It contains both Jupyter notebooks and raw source code, covering a broad range of tasks: from basic machine-learning and neural-network models to more advanced use cases, using both TensorFlow v1 and v2 APIs. For clarity and educational value, each example is accompanied by explanatory comments or markdown cells to illustrate what the code does and why — a design that makes it especially suitable for self-learners or students following along with real data. Besides raw implementations, the repo often shows best practices using higher-level constructs (e.g. dataset pipelines, estimators, layers) which reflect modern TensorFlow workflows rather than only textbook-style code. -
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tmi.js
Javascript library for the Twitch Messaging Interface
...If the identity has special permission from Twitch for a higher join rate then you should implement your own calls to the client.join method. Disable receiving JOIN/PART events for other users. Good for decreasing network traffic when joining lots of channels or you don't care about this data. After a threshold per channel Twitch stops sending this data so it may not be necessary for all cases. Channels to automatically join upon connecting. The rate of joins is controlled by the options.joinInterval option. Automatically reconnect the client if it gets disconnected for any reason. ... -
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MarvelHeroes
A sample Marvel heroes application based on MVVM
MarvelHeroes is a demo application based on modern Android application tech-stacks and MVVM architecture. Fetching data from the network and integrating persisted data in the database via repository pattern. -
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Arraymancer
A fast, ergonomic and portable tensor library in Nim
Arraymancer is a tensor and deep learning library for the Nim programming language, designed for high-performance numerical computations and machine learning applications. -
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Minkowski Engine
Auto-diff neural network library for high-dimensional sparse tensors
...Compressing a neural network to speed up inference and minimize memory footprint has been studied widely. One of the popular techniques for model compression is pruning the weights in convnets, is also known as sparse convolutional networks. Such parameter-space sparsity used for model compression compresses networks that operate on dense tensors and all intermediate activations of these networks are also dense tensors. -
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textures.js
SVG patterns for data visualization
Textures.js is a JavaScript library for creating SVG patterns. Made on top of d3.js, it is designed for data visualization. Import textures.js from NPM. You can also use textures.js in your HTML page with a <script> tag by downloading textures.js to a local folder or by using the Unpkg CDN network. Textures.js can be used alongside d3.
