Search Results for "linux gpib support" - Page 3
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Showing 127 open source projects for "linux gpib support"
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Fully Managed MySQL, PostgreSQL, and SQL ServerCloud SQL handles your database ops end to end, so you can focus on your app.
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Theseus
A library for differentiable nonlinear optimization
Theseus is a library for differentiable nonlinear optimization that lets you embed solvers like Gauss-Newton or Levenberg–Marquardt inside PyTorch models. Problems are expressed as factor graphs with variables on manifolds (e.g., SE(3), SO(3)), so classical robotics and vision tasks—bundle adjustment, pose graph optimization, hand–eye calibration—can be written succinctly and solved efficiently. Because solves are differentiable, you can backpropagate through optimization to learn cost... -
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MediaManager
A modern selfhosted media management system for your media library
MediaManager is a modern, self-hosted media management system that unifies and replaces the traditional “ARR” stack with a single, cohesive platform for discovering, organizing, and automating TV and movie libraries. Rather than relying on separate tools patched together, MediaManager offers a streamlined interface and workflow where media metadata, collection insights, and automation policies live side-by-side in one system. It is designed for ease of deployment with Docker, supports... -
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Kornia
Open Source Differentiable Computer Vision Library
Kornia is a differentiable computer vision library for PyTorch. It consists of a set of routines and differentiable modules to solve generic computer vision problems. At its core, the package uses PyTorch as its main backend both for efficiency and to take advantage of the reverse-mode auto-differentiation to define and compute the gradient of complex functions. Inspired by existing packages, this library is composed by a subset of packages containing operators that can be inserted within... -
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Claude Quickstarts
A collection of projects for building deployable applications
Claude Quickstarts is a curated collection of starter projects and templates that help developers quickly begin building applications with the Claude API, making it easier to leverage Anthropic’s Claude models for real use cases. Each quickstart provides a foundational codebase with preconfigured settings and examples for common deployment scenarios, so developers can focus on customizing functionality instead of bootstrapping infrastructure. The repository includes demos, sample... -
Gemini 3 and 200+ AI Models on One PlatformBuild generative AI apps with Vertex AI. Switch between models without switching platforms.
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Playground Cheatsheet for Python
Playground and cheatsheet for learning Python
learn-python is another repository by Oleksii Trekhleb that serves as both a playground and an interactive cheatsheet for learning Python. It contains numerous Python scripts organized by topic (lists, dictionaries, loops, functions, classes, modules, etc.), each with code examples, explanations, test assertions, and links to further readings. The design supports “learn by doing”: you can modify the code, run the tests, see how behavior changes, and thus internalize Python language features,... -
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NSync
nsync is a C library that exports various synchronization primitives
nsync is a portable C library that provides a collection of advanced synchronization primitives designed to facilitate safe and efficient multithreaded programming. It offers reader-writer locks, condition variables, run-once initialization, waitable counters, and waitable bits for coordination and cancellation between threads. Unlike traditional pthreads-based synchronization, nsync introduces conditional critical sections, allowing developers to wait for arbitrary conditions without... -
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PennyLane
A cross-platform Python library for differentiable programming
A cross-platform Python library for differentiable programming of quantum computers. Train a quantum computer the same way as a neural network. Built-in automatic differentiation of quantum circuits, using the near-term quantum devices directly. You can combine multiple quantum devices with classical processing arbitrarily! Support for hybrid quantum and classical models, and compatible with existing machine learning libraries. Quantum circuits can be set up to interface with either NumPy,... -
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Claude Code Plugins Directory
Official, Anthropic-managed directory of high quality Claude Plugins
Claude Code Plugins Directory repository provides a collection of plugins intended to extend Claude’s capabilities by turning the model into a specialized assistant tailored to specific workflows, teams, or organizational needs. These plugins define how Claude should access tools, retrieve data, and execute structured tasks so that outputs become more consistent and production-ready. The project emphasizes customizable automation by allowing developers to encode preferred workflows, domain... -
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Awesome Free ChatGPT
List of free ChatGPT mirror sites, continuously updated
This is a curated directory of freely accessible ChatGPT-style services and mirror sites that offer AI chatbot interfaces without login or payment requirements. Resources often support multiple models like GPT-4, Claude, Gemini, and more. Data collected from multiple independent sites with descriptions and tags. Includes services with image upload and drawing capabilities. Aggregates free, no-login-required ChatGPT-like web services. Continually updated mirror list to maintain availability. -
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AutoKeras
AutoML library for deep learning
AutoKeras: An AutoML system based on Keras. It is developed by DATA Lab at Texas A&M University. The goal of AutoKeras is to make machine learning accessible to everyone. AutoKeras only support Python 3. If you followed previous steps to use virtualenv to install tensorflow, you can just activate the virtualenv. Currently, AutoKeras is only compatible with Python >= 3.7 and TensorFlow >= 2.8.0. AutoKeras supports several tasks with extremely simple interface. AutoKeras would search for the... -
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Mimesis
High-performance fake data generator for Python
Mimesis is an open source high-performance fake data generator for Python, able to provide data for various purposes in various languages. It's currently the fastest fake data generator for Python, and supports many different data providers that can produce data related to people, food, transportation, internet and many more. Mimesis is really easy to use, with everything you need just an import away. Simply import an object, called a Provider, which represents the type of data you... -
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Shumai
Fast Differentiable Tensor Library in JavaScript & TypeScript with Bun
Shumai is an experimental differentiable tensor library for TypeScript and JavaScript, developed by Facebook Research. It provides a high-performance framework for numerical computing and machine learning within modern JavaScript runtimes. Built on Bun and Flashlight, with ArrayFire as its numerical backend, Shumai brings GPU-accelerated tensor operations, automatic differentiation, and scientific computing tools directly to JavaScript developers. It allows seamless integration of machine... -
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Professional Services
Common solutions and tools developed by Google Cloud
Professional Services repository is a collection of real-world solutions, tools, and reference implementations developed by Google Cloud’s Professional Services team to address common enterprise challenges. Unlike simple sample repositories, it focuses on production-oriented use cases such as data pipelines, machine learning workflows, infrastructure automation, and security management. The repository contains a wide variety of projects, including tools for validating data migrations,... -
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Recursive Language Models
General plug-and-play inference library for Recursive Language Models
RLM (short for Reinforcement Learning Models) is a modular framework that makes it easier to build, train, evaluate, and deploy reinforcement learning (RL) agents across a wide range of environments and tasks. It provides a consistent API that abstracts away many of the repetitive engineering patterns in RL research and application work, letting developers focus on modeling, experimentation, and fine-tuning rather than infrastructure plumbing. Within the framework, you can define custom... -
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Nevergrad
A Python toolbox for performing gradient-free optimization
Nevergrad is a Python library for derivative-free optimization, offering robust implementations of many algorithms suited for black-box functions (i.e. functions where gradients are unavailable or unreliable). It targets hyperparameter search, architecture search, control problems, and experimental tuning—domains in which gradient-based methods may fail or be inapplicable. The library provides an easy interface to define an optimization problem (parameter space, loss function, budget) and... -
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CoreNet
CoreNet: A library for training deep neural networks
CoreNet is Apple’s internal deep learning framework for distributed neural network training, designed for high scalability, low-latency communication, and strong hardware efficiency. It focuses on enabling large-scale model training across clusters of GPUs and accelerators by optimizing data flow and parallelism strategies. CoreNet provides abstractions for data, tensor, and pipeline parallelism, allowing models to scale without code duplication or heavy manual configuration. Its distributed... -
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zpdf
Zero-copy PDF text extraction library written in Zig
zpdf is a high-performance PDF text extraction library written in Zig that focuses on speed, low overhead, and modern parsing techniques. It leans heavily on memory-mapped file reading and zero-copy patterns where possible, so it can scan large PDFs without repeatedly copying data around in memory. The library supports streaming extraction using efficient arena allocation, making it well suited for workloads that need to process big documents quickly or in batches. It implements multiple PDF... -
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Lightly
A python library for self-supervised learning on images
A python library for self-supervised learning on images. We, at Lightly, are passionate engineers who want to make deep learning more efficient. That's why - together with our community - we want to popularize the use of self-supervised methods to understand and curate raw image data. Our solution can be applied before any data annotation step and the learned representations can be used to visualize and analyze datasets. This allows selecting the best core set of samples for model training... -
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pythondialog
Python module to build dialogs for terminal-based applications
This is a Python module for doing terminal-based user interaction. It wraps the dialog/Xdialog program, and provides a nice, object-oriented programming model. -
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bidict
The bidirectional mapping library for Python
Depended on by Google, Venmo, CERN, Baidu, Tencent, and teams across the world since 2009. Familiar, Pythonic APIs that are carefully designed for safety, simplicity, flexibility, and ergonomics. Lightweight, with no runtime dependencies outside Python's standard library. Implemented in concise, well-factored, fully type-hinted Python code that is optimized for running efficiently as well as for long-term maintenance and stability. Extensively documented. 100% test coverage running... -
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Empact Foundation Class Library
Cross-platform C++ library for use as a default application framework.
...Features include: * Threading & synchronization * Socket programming: SSL, NanoMsg & ZMQ * File I/O utilities: zlib, ini, yaml * Native Database access: MySQL, SQLite, BerkleyDB, Postgre, REDIS and ODBC * Built-in mini XML parser; optional EXPAT, LIBXML and MSXML support * Network protocol stack: HTTP, FTP, SMTP, POP3, SOAP, XMLRPC * Scripting languages: Perl, Python, JavaScript, VBScript, Java, Lua, TCL, Squirrel * Cloud Computing: AWS * Encryption: OpenSSL * Platforms: Linux/Posix, Windows, Arduino * Over 500+ highly reusable classes. 4000+ fully documented functions. Follow the 'Wiki' link above to explore everything about the framework. -
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MMDeploy
OpenMMLab Model Deployment Framework
MMDeploy is an open-source deep learning model deployment toolset. It is a part of the OpenMMLab project. Models can be exported and run in several backends, and more will be compatible. All kinds of modules in the SDK can be extended, such as Transform for image processing, Net for Neural Network inference, Module for postprocessing and so on. Install and build your target backend. ONNX Runtime is a cross-platform inference and training accelerator compatible with many popular ML/DNN... -
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Glumpy
Python+Numpy+OpenGL, scalable and beautiful scientific visualization
Glumpy is a Python library that simplifies the development of high-performance, interactive OpenGL visualizations. It abstracts complex OpenGL tasks into Pythonic constructs, making it easier for scientists, artists, and developers to harness the power of the GPU for real-time rendering and data visualization. Glumpy is particularly well-suited for rapid prototyping of graphical applications, and its integration with NumPy and shader programming makes it a powerful tool for both research and... -
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eCxx
A C++ library for AVR and NodeMCU
...On one side, eCxx supports the original megaAVR series (ATmega328P, ATmega1284P, ATmega2560, ATmega32U4, AT90USB1286, etc.) as well as the new megaAVR 0-Series (ATmega4808, ATmega4809, etc.). On the other side, while eCxx is primarily designed to work in NodeMCU, it should also support other ESP-12 based design as well as ESP-01 based design. The Makefile build system and some of the tools would only run on Linux. However, the library source code should be portable enough to be built using other build systems for AVR and NodeMC -
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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'...
