Search Results for "virtual-machine" - Page 5
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Showing 5199 open source projects for "virtual-machine"
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The Unsplash Dataset
Unsplash images made available for research and machine learning
The Unsplash Dataset is made up of over 350,000+ contributing global photographers and data sourced from hundreds of millions of searches across a nearly unlimited number of uses and contexts. Due to the breadth of intent and semantics contained within the Unsplash dataset, it enables new opportunities for research and learning. -
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OpenVINO Training Extensions
Trainable models and NN optimization tools
OpenVINO™ Training Extensions provide a convenient environment to train Deep Learning models and convert them using the OpenVINO™ toolkit for optimized inference. When ote_cli is installed in the virtual environment, you can use the ote command line interface to perform various actions for templates related to the chosen task type, such as running, training, evaluating, exporting, etc. ote train trains a model (a particular model template) on a dataset and saves results in two files. ote optimize optimizes a pre-trained model using NNCF or POT depending on the model format. ... -
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RevoGrid
Powerful virtual data grid smartsheet with advanced customization
Support Millions of cells and thousands of columns easy and efficiently for fast data rendering. Easy to use. For large organizations managing massive datasets. Performance and scalability to handle even the most complex data tables. Rapid prototyping with intuitive and extendable codebase. Agility to build robust data-driven applications in no time. Quickly build elegant and efficient data grids. Lightweight yet powerful architecture lets you easily scale as your needs grow. -
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CatBoost
High-performance library for gradient boosting on decision trees
CatBoost is a fast, high-performance open source library for gradient boosting on decision trees. It is a machine learning method with plenty of applications, including ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. CatBoost offers superior performance over other GBDT libraries on many datasets, and has several superb features. It has best in class prediction speed, supports both numerical and categorical features, has a fast and scalable GPU version, and readily comes with visualization tools. ... -
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ffmpeg-over-ip
Connect to remote ffmpeg servers
ffmpeg-over-ip is a client-server system that enables remote execution of FFmpeg commands on a machine with GPU access while controlling it from another environment such as a container or virtual machine. It allows applications without direct GPU access to offload video transcoding tasks to a remote server, improving performance without requiring complex passthrough setups. The system works by coordinating commands through a lightweight protocol while using a shared filesystem to exchange media data. ... -
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MCiSEE
All of Minecraft, EASILY get Minecraft resources
...It bridges the gap between game simulation and AI experimentation by providing tools that connect Minecraft gameplay with external algorithms. Developers can extend the platform to test new approaches to artificial intelligence within a complex virtual environment. -
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Nodeenv
Virtual environment for Node.js & integrator with virtualenv
A Python tool that creates isolated Node.js virtual environments, similar to Python's virtualenv. -
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Expr
Expression language and expression evaluation for Go
Expr package provides an engine that can compile and evaluate expressions. An expression is a one-liner that returns a value (mostly, but not limited to, booleans). It is designed for simplicity, speed and safety. The purpose of the package is to allow users to use expressions inside configuration for more complex logic. It is a perfect candidate for the foundation of a business rule engine. The idea is to let configure things in a dynamic way without recompile of a program. -
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PostfixAdmin
Web based virtual user administration interface for Postfix mail
PostfixAdmin is a web-based interface for managing mail domains, mailboxes, and aliases for Postfix mail servers. It allows administrators to add and configure virtual domains and email users easily, supporting MySQL, PostgreSQL, and SQLite as backend databases. It's widely used in self-hosted email setups for simplifying email management. -
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handson-ml3
Fundamentals of Machine Learning and Deep Learning
handson-ml3 contains the Jupyter notebooks and code for the third edition of the book Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow. It guides readers through modern machine learning and deep learning workflows using Python, with examples spanning data preparation, supervised and unsupervised learning, deep neural networks, RL, and production-ready model deployment. The third edition updates the content for TensorFlow 2 and Keras, introduces new chapters (for example on reinforcement learning or generative models), and offers best-practice code that reflects current ecosystems. ... -
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Gradio
Create UIs for your machine learning model in Python in 3 minutes
Gradio is the fastest way to demo your machine learning model with a friendly web interface so that anyone can use it, anywhere! Gradio can be installed with pip. Creating a Gradio interface only requires adding a couple lines of code to your project. You can choose from a variety of interface types to interface your function. Gradio can be embedded in Python notebooks or presented as a webpage. -
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ggml
Tensor library for machine learning
ggml is an open-source tensor library designed for efficient machine learning computation with a focus on running models locally and with minimal dependencies. Written primarily in C and C++, the library provides low-level tensor operations and automatic differentiation that allow developers to implement machine learning algorithms and neural networks efficiently. The project emphasizes portability and performance, enabling machine learning inference across a wide range of hardware environments including CPUs and specialized accelerators. ... -
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CML
Continuous Machine Learning | CI/CD for ML
Continuous Machine Learning (CML) is an open-source CLI tool for implementing continuous integration & delivery (CI/CD) with a focus on MLOps. Use it to automate development workflows, including machine provisioning, model training and evaluation, comparing ML experiments across project history, and monitoring changing datasets. CML can help train and evaluate models, and then generate a visual report with results and metrics, automatically on every pull request. -
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Otter-Grader
A Python and R autograding solution
...Otter supports local grading through parallel Docker containers, grading using the autograder platforms of 3rd party learning management systems (LMSs), the deployment of an Otter-managed grading virtual machine, and a client package that allows students to run public checks on their own machines. Otter is designed to grade Python scripts and Jupyter Notebooks, and is compatible with a few different LMSs, including Canvas and Gradescope. -
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Vectras-VM-Android
A virtual machine app for Android based on QEMU.
Welcome to Vectras VM! A virtual machine app for Android based on QEMU that lets you emulate various OSes including Windows, macOS, Linux, and Android. -
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OpenCV
Open Source Computer Vision Library
OpenCV (Open Source Computer Vision Library) is a comprehensive open-source library for computer vision, machine learning, and image processing. It enables developers to build real-time vision applications ranging from facial recognition to object tracking. OpenCV supports a wide range of programming languages including C++, Python, and Java, and is optimized for both CPU and GPU operations. -
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XUnity Auto Translator
Advanced translator plugin that can be used to translate Unity games
XUnity.AutoTranslator is an advanced plugin framework designed to automatically translate text in Unity-based games in real time by intercepting and replacing in-game text during rendering. It works by injecting itself into the game process and leveraging external translation services such as Google Translate, DeepL, or custom APIs to dynamically convert text into a target language. The tool supports both automatic translation and manual translation workflows, allowing users to refine or... -
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MLJ.jl
A Julia machine learning framework
MLJ (Machine Learning in Julia) is a toolbox written in Julia providing a common interface and meta-algorithms for selecting, tuning, evaluating, composing, and comparing about 200 machine learning models written in Julia and other languages. The functionality of MLJ is distributed over several repositories illustrated in the dependency chart below. -
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SageMaker Python SDK
Training and deploying machine learning models on Amazon SageMaker
SageMaker Python SDK is an open source library for training and deploying machine learning models on Amazon SageMaker. With the SDK, you can train and deploy models using popular deep learning frameworks Apache MXNet and TensorFlow. You can also train and deploy models with Amazon algorithms, which are scalable implementations of core machine learning algorithms that are optimized for SageMaker and GPU training. -
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MatlabMachine
Machine learning algorithms
Matlab-Machine is a comprehensive collection of machine learning algorithms implemented in MATLAB. It includes both basic and advanced techniques for classification, regression, clustering, and dimensionality reduction. Designed for educational and research purposes, the repository provides clear implementations that help users understand core ML concepts. -
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PDFMathTranslate
PDF scientific paper translation with preserved formats
PDFMathTranslate is a Python-based tool that uses AI translation to convert academic PDFs into bilingual (e.g. Chinese-English) documents while preserving formatting, including math notation. It supports OCR-enhanced content and offers CLI, GUI, Docker, and Zotero integration under AGPL v3. -
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Hex
Package manager for the Erlang ecosystem
Hex is the official package manager for the Erlang ecosystem, supporting languages like Elixir and Erlang that run on the BEAM virtual machine. It integrates seamlessly with build tools such as Mix and Rebar3, allowing developers to fetch, publish, and manage packages efficiently. Hex provides a centralized repository, ensuring that packages are easily discoverable and maintainable, thereby streamlining the development workflow within the BEAM community. -
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XMRig Proxy
Monero (XMR) Stratum protocol proxy
Extremely high-performance CryptoNote stratum protocol proxy. Works with any pool and any miner with nicehash support. Can easily handle over 100K connections on a cheap $5 (1024 MB) virtual machine. Reduce the number of pool connections up to 256 times, 100K workers become just 391 workers on the pool side. Written on C++/libuv same as XMRig miner. -
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Orion
A machine learning library for detecting anomalies in signals
Orion is a machine-learning library built for unsupervised time series anomaly detection. Such signals are generated by a wide variety of systems, few examples include telemetry data generated by satellites, signals from wind turbines, and even stock market price tickers. We built this to provide one place where users can find the latest and greatest in machine learning and deep learning world including our own innovations. -
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Scholar
Traditional machine learning on top of Nx
Traditional machine learning tools built on top of Nx. Scholar implements several algorithms for classification, regression, clustering, dimensionality reduction, metrics, and preprocessing.
