Search Results for "data capture framework" - Page 41

Showing 2706 open source projects for "data capture framework"

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  • 1
    Kinetic.jl

    Kinetic.jl

    Universal modeling and simulation of fluid mechanics upon ML

    Kinetic is a computational fluid dynamics toolbox written in Julia. It aims to furnish efficient modeling and simulation methodologies for fluid dynamics, augmented by the power of machine learning. Based on differentiable programming, mechanical and neural network models are fused and solved in a unified framework. Simultaneous 1-3 dimensional numerical simulations can be performed on CPUs and GPUs.
    Downloads: 9 This Week
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  • 2
    fastMRI

    fastMRI

    A large open dataset + tools to speed up MRI scans using ML

    ...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 loaders, subsampling utilities, reconstruction models, and evaluation metrics, supporting both research reproducibility and practical experimentation. It includes reference implementations for key MRI reconstruction architectures such as U-Net and Variational Networks (VarNet), along with example scripts for model training and evaluation using the PyTorch Lightning framework. ...
    Downloads: 0 This Week
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  • 3
    PromethAI

    PromethAI

    Open-source framework that gives you AI Agents

    PromethAI-Backend is a backend framework for AI-driven automation and knowledge extraction. It is designed to integrate with large language models (LLMs) to provide AI-enhanced workflows, including content generation, summarization, and data analysis.
    Downloads: 0 This Week
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  • 4
    Northwind Traders

    Northwind Traders

    Northwind Traders is a sample application built using ASP.NET Core

    Northwind Traders is a sample business application created to demonstrate Clean Architecture in .NET Core. It separates domain rules, application logic, persistence, infrastructure, and presentation into distinct projects. The backend uses Entity Framework Core, while an Angular client provides the browser interface. MediatR organizes commands and queries, with FluentValidation handling request rules and AutoMapper translating data models. The solution also includes authentication support and automated tests for key application behavior. It is best used as an educational reference or starting point rather than a maintained production template. ...
    Downloads: 0 This Week
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  • 5
    Lightning Flash

    Lightning Flash

    Flash enables you to easily configure and run complex AI recipes

    Your PyTorch AI Factory, Flash enables you to easily configure and run complex AI recipes for over 15 tasks across 7 data domains. In a nutshell, Flash is the production-grade research framework you always dreamed of but didn't have time to build. All data loading in Flash is performed via a from_* classmethod on a DataModule. Which DataModule to use and which from_* methods are available depends on the task you want to perform. For example, for image segmentation where your data is stored in folders, you would use the from_folders method of the SemanticSegmentationData class. ...
    Downloads: 0 This Week
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  • 6
    wxMathPlot
    wxMathPlot is an add-on library for wxWidgets which provides a framework for easy plotting of mathematical functions, sampled data and generic 2D plots.
    Downloads: 6 This Week
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  • 7
    Horovod

    Horovod

    Distributed training framework for TensorFlow, Keras, PyTorch, etc.

    ...Horovod can be installed on-premise or run out-of-the-box in cloud platforms, including AWS, Azure, and Databricks. Horovod can additionally run on top of Apache Spark, making it possible to unify data processing and model training into a single pipeline. Once Horovod has been configured, the same infrastructure can be used to train models with any framework, making it easy to switch between TensorFlow, PyTorch, MXNet, and future frameworks as machine learning tech stacks continue to evolve. Start scaling your model training with just a few lines of Python code. ...
    Downloads: 5 This Week
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  • 8
    Metaseq

    Metaseq

    Repo for external large-scale work

    Metaseq is a flexible, high-performance framework for training and serving large-scale sequence models, such as language models, translation systems, and instruction-tuned LLMs. Built on top of PyTorch, it provides distributed training, model sharding, mixed-precision computation, and memory-efficient checkpointing to support models with hundreds of billions of parameters. The framework was used internally at Meta to train models like OPT (Open Pre-trained Transformer) and serves as a reference implementation for scaling transformer architectures efficiently across GPUs and nodes. ...
    Downloads: 0 This Week
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  • 9

    DpdlScripting

    DPDL (Dynamic Packet Definition Language) is a small framework library

    Dpdl (Dynamic Packet Definition Language) is a constraint device framework and scripting engine that can be used to implement small, portable and light-weight applications on Java enabled devices (in particular J2ME and JavaME) and small embedded systems. It has been developed in 2002, in early days when mobile phones where running mostly J2ME applications. Dpdl is a compact framework, small memory footprint library and scripting engine that can be used to encode, decode, control and query data efficiently on limited memory devices. ...
    Downloads: 0 This Week
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  • 10
    aqueduct LLM

    aqueduct LLM

    Aqueduct allows you to run LLM and ML workloads on any infrastructure

    Aqueduct is an MLOps framework that allows you to define and deploy machine learning and LLM workloads on any cloud infrastructure. Aqueduct is an open-source MLOps framework that allows you to write code in vanilla Python, run that code on any cloud infrastructure you'd like to use, and gain visibility into the execution and performance of your models and predictions. Aqueduct's Python native API allows you to define ML tasks in regular Python code. You can connect Aqueduct to your existing...
    Downloads: 0 This Week
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  • 11
    iJEPA

    iJEPA

    Official codebase for I-JEPA

    ...The design scales naturally with Vision Transformer backbones and flexible masking strategies, and it trains stably at large batch sizes. i-JEPA’s predictions are made in embedding space, which is computationally efficient and better aligned with downstream discrimination tasks. The repository provides training recipes, data pipelines, and evaluation code that clarify which masking patterns and architectural choices matter most.
    Downloads: 1 This Week
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  • 12
    AB3DMOT

    AB3DMOT

    Official Python Implementation for "3D Multi-Object Tracking

    AB3DMOT is a real-time 3D multi-object tracking framework designed for applications such as autonomous driving and robotics perception. The system processes detection results from 3D object detectors that analyze LiDAR point clouds and uses them to track multiple objects across consecutive frames. Its tracking pipeline relies on a combination of classical algorithms, including a Kalman filter for state estimation and the Hungarian algorithm for data association between detected objects and existing tracks. ...
    Downloads: 0 This Week
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  • 13
    langchain-prefect

    langchain-prefect

    Tools for using Langchain with Prefect

    ...We need to know details about how our apps work, even when we want to use tools with convenient abstractions that may obfuscate those details. Prefect is built to help data people build, run, and observe event-driven workflows wherever they want. It provides a framework for creating deployments on a whole slew of runtime environments (from Lambda to Kubernetes), and is cloud agnostic (best supports AWS, GCP, Azure). For this reason, it could be a great fit for observing apps that use LLMs. RecordLLMCalls is a ContextDecorator that can be used to track LLM calls made by Langchain LLMs as Prefect flows. ...
    Downloads: 0 This Week
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  • 14

    Network Instrument Workbench

    Script driven framework for Prologix GPIB - Lan adapter & more

    A layered set of functions to abstract the Prologix command set into an easy to use bash shell script format. To provide access to and control of electronic test equipment, initially for data logging applications. Functions to configure, send commands, data and status. Also to provides functionality for direct access to other network enabled equipment. Command line and makefile environment. Developed under FreeBSD, but built and tested without code change under Debian, XUbuntu and Devuan Linux. Overall, the aim is to provide some of the control functionality and simplicity of the old HP Basic instrument control framework, accessable from any machine on the network. ...
    Downloads: 0 This Week
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  • 15
    FluentLenium

    FluentLenium

    FluentLenium is a web & mobile automation framework

    FluentLenium is a React-ready website automation framework that extends Selenium to write readable, reusable, reliable and resilient UI functional tests. It’s written and maintained by people who are automating browser-based tests on a daily basis. FluentLenium provides a Java-fluent interface to Selenium, and brings some magic to avoid common issues faced by Selenium users. FluentLenium is shipped with adapters for JUnit4, JUnit5, TestNG, Spock, Spring TestNG, Cucumber and Kotest, but it...
    Downloads: 0 This Week
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  • 16
    Spektral

    Spektral

    Graph Neural Networks with Keras and Tensorflow 2

    Spektral is a Python library for graph deep learning, based on the Keras API and TensorFlow 2. The main goal of this project is to provide a simple but flexible framework for creating graph neural networks (GNNs). You can use Spektral for classifying the users of a social network, predicting molecular properties, generating new graphs with GANs, clustering nodes, predicting links, and any other task where data is described by graphs. Spektral implements some of the most popular layers for graph deep learning. ...
    Downloads: 0 This Week
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  • 17
    The HaskellR project

    The HaskellR project

    The full power of R in Haskell

    The HaskellR project provides an environment for efficiently processing data using Haskell or R code, interchangeably. HaskellR allows Haskell functions to seamlessly call R functions and vice versa. It provides the Haskell programmer with the full breadth of existing R libraries and extensions for numerical computation, statistical analysis and machine learning. Optionally, pass in the --nix flag to all commands if you have the Nix package manager installed. Nix can populate a local build...
    Downloads: 0 This Week
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  • 18
    The Related Values Processing Framework helps the integration of Process Control Data Historian Systems.
    Downloads: 0 This Week
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  • 19
    crawly

    crawly

    High-level web crawling and scraping framework for Elixir apps

    Crawly is a high-level application framework for crawling websites and extracting structured data using the Elixir programming language. It provides a complete environment for building web crawlers that systematically visit pages, collect information, and transform that data into structured formats for further processing. Crawly is designed for tasks such as data mining, information processing, and building historical archives of web content.
    Downloads: 4 This Week
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  • 20
    AI-Agent-Host

    AI-Agent-Host

    The AI Agent Host is a module-based development environment.

    ...The AI Agent Host is a module-based environment designed to facilitate rapid experimentation and testing. It includes a docker-compose configuration with QuestDB, Grafana, Code-Server and Nginx. The AI Agent Host provides a seamless interface for managing and querying data, visualizing results, and coding in real-time. The AI Agent Host is built specifically for LangChain, a framework dedicated to developing applications powered by language models. LangChain recognizes that the most powerful and distinctive applications go beyond simply utilizing a language model and strive to be data-aware and agentic. ...
    Downloads: 0 This Week
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  • 21
    OpenCombine

    OpenCombine

    Open source implementation of Apple's Combine framework

    OpenCombine is an open-source implementation of Apple’s Combine framework, providing a reactive programming model for handling asynchronous data streams in Swift across multiple platforms. It replicates the core concepts of Combine, such as publishers, subscribers, and operators, enabling developers to process values over time in a declarative and composable way. One of its primary goals is compatibility, allowing developers to use Combine-like APIs on platforms where Apple’s official implementation is unavailable, including older Apple operating systems, Linux, Windows, and WebAssembly environments. ...
    Downloads: 0 This Week
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  • 22
    Hippo4j

    Hippo4j

    Powerful dynamic thread pool framework with monitoring/alarm functions

    Dynamically observable thread pool framework to improve online operation guarantee capabilities for business systems. Dynamically change thread pool parameters when the application is running, including not limited to core, maximum thread, blocking queue size, and rejection strategy, etc., and support different node thread pool configuration differentiation under the application cluster.
    Downloads: 0 This Week
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  • 23

    4WS Warp

    Development of extjs based rich web applications

    Warp is an open source framework that can be used to develop Java based applications, using Java and JEE5. It allows to develop Desktop Applications or 3 Tier Applications based on Swing extensions or Rich web applications based on ExtJS and JAX-RS (Restful web services). Business logic and data access tiers can be developed using JPA or JDBC and EJB 3 or any other Java based technology.
    Downloads: 1 This Week
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  • 24
    Mars Framework

    Mars Framework

    Mars is a tensor-based unified framework for large-scale data

    Mars is a distributed computing framework designed to scale scientific computing and data science workloads across large clusters while preserving the familiar programming interfaces of common Python libraries. The project provides a tensor-based execution model that extends the capabilities of tools such as NumPy, pandas, and scikit-learn so that large datasets can be processed in parallel without rewriting code for distributed environments.
    Downloads: 8 This Week
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  • 25
    canvas-sketch

    canvas-sketch

    Framework for making generative artwork in JavaScript and the browser

    ...It integrates smoothly with modern JavaScript workflows and supports modular development patterns. The framework is commonly used in creative coding communities for sketches, data visualizations, and interactive installations. Overall, canvas-sketch serves as a productivity-focused foundation for browser-based visual experimentation and rapid iteration.
    Downloads: 0 This Week
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