Search Results for "virtual-machine" - Page 8
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Showing 2278 open source projects for "virtual-machine"
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Train ML Models With SQL You Already KnowBuild and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
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Go from Code to Production URL in SecondsSkip the Kubernetes configs. Cloud Run handles HTTPS, scaling, and infrastructure automatically. Two million requests free per month.
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Volcano
A Cloud Native Batch System (Project under CNCF)
Volcano is a batch system built on Kubernetes. It provides a suite of mechanisms that are commonly required by many classes of batch & elastic workload including machine learning/deep learning, bioinformatics/genomics, and other "big data" applications. These types of applications typically run on generalized domain frameworks like TensorFlow, Spark, Ray, PyTorch, MPI, etc, which Volcano integrates with. Volcano builds upon a decade and a half of experience running a wide variety of high-performance workloads at scale using several systems and platforms, combined with best-of-breed ideas and practices from the open-source community. ... -
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Metaflow
A framework for real-life data science
Metaflow is a human-friendly Python library that helps scientists and engineers build and manage real-life data science projects. Metaflow was originally developed at Netflix to boost productivity of data scientists who work on a wide variety of projects from classical statistics to state-of-the-art deep learning. -
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Elixir
Dynamic, functional language designed for building scalable apps
...All Elixir code runs inside lightweight threads of execution (called processes) that are isolated and exchange information via messages. Due to their lightweight nature, it is not uncommon to have hundreds of thousands of processes running concurrently in the same machine. Isolation allows processes to be garbage collected independently, reducing system-wide pauses, and using all machine resources as efficiently as possible (vertical scaling). Processes are also able to communicate with other processes running on different machines in the same network. -
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PackageCompiler
Compile your Julia Package
...You can save loaded packages and compiled functions into a file (called a sysimage) that you pass to Julia upon startup. Typically the goal is to reduce latency on your machine; for example, you could load the packages and compile the functions used in common plotting workflows using that saved image by default. In general, sysimages are not relocatable to other machines; they'll only work on the machine they were created on. -
Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
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Deepchecks
Test Suites for validating ML models & data
Deepchecks is the leading tool for testing and for validating your machine learning models and data, and it enables doing so with minimal effort. Deepchecks accompany you through various validation and testing needs such as verifying your data’s integrity, inspecting its distributions, validating data splits, evaluating your model and comparing between different models. While you’re in the research phase, and want to validate your data, find potential methodological problems, and/or validate your model and evaluate it. ... -
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IVY
The Unified Machine Learning Framework
Take any code that you'd like to include. For example, an existing TensorFlow model, and some useful functions from both PyTorch and NumPy libraries. Choose any framework for writing your higher-level pipeline, including data loading, distributed training, analytics, logging, visualization etc. Choose any backend framework which should be used under the hood, for running this entire pipeline. Choose the most appropriate device or combination of devices for your needs. DeepMind releases an... -
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TensorFlow Model Garden
Models and examples built with TensorFlow
The TensorFlow Model Garden is a repository with a number of different implementations of state-of-the-art (SOTA) models and modeling solutions for TensorFlow users. We aim to demonstrate the best practices for modeling so that TensorFlow users can take full advantage of TensorFlow for their research and product development. To improve the transparency and reproducibility of our models, training logs on TensorBoard.dev are also provided for models to the extent possible though not all models... -
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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... -
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MAME
MAME is a multi-purpose emulation framework
...The fact that the software is usable serves primarily to validate the accuracy of the documentation (how else can you prove that you have recreated the hardware faithfully?). Over time, MAME (originally stood for Multiple Arcade Machine Emulator) absorbed the sister-project MESS (Multi Emulator Super System), so MAME now documents a wide variety of (mostly vintage) computers, video game consoles and calculators, in addition to the arcade video games that were its initial focus. The MAME project as a whole is distributed under the terms of the GNU General Public License, 2 (GPL-2.0), since it contains code made available under multiple GPL-compatible licenses. -
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Agora Flat
Project flat is the Web, Windows and macOS client of Agora Flat
Agora Flat Open Source Virtual Classroom. Battery included online tutoring tools for teachers & freelance trainers. Build real-time interactive virtual classroom with ease from our open-sourced projects. Agora Flat was born out of an exploratory project in which we investigated customer needs and user experience. After receiving good internal feedback, we believe that Flat has the potential to become an online classroom product that can really help people and have a good user experience. ... -
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MediaPipe
Cross-platform, customizable ML solutions for live and streaming media
...Provides segmentation masks for prominent humans in the scene. MediaPipe Face Mesh is a face geometry solution that estimates 468 3D face landmarks in real-time even on mobile devices. It employs machine learning (ML) to infer the 3D surface geometry, requiring only a single camera input without the need for a dedicated depth sensor. Utilizing lightweight model architectures together with GPU acceleration throughout the pipeline, the solution delivers real-time performance-critical for live experiences. Human pose estimation from video plays a critical role in various applications such as quantifying physical exercises, sign language recognition, and full-body gesture control. ... -
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wa-sqlite
WebAssembly SQLite with support for browser storage extensions
wa-sqlite is a WebAssembly build of SQLite that enables developers to run a fully functional relational database engine inside web browsers or other JavaScript environments. Unlike traditional SQLite builds, this project emphasizes extensibility by allowing developers to implement custom virtual file systems entirely in JavaScript, which enables flexible storage backends such as IndexedDB or the Origin Private File System. This design allows applications to persist data locally in a browser while maintaining the familiar SQL interface and behavior of SQLite. The project supports both synchronous and asynchronous execution models, accommodating different performance and architectural needs, including asynchronous APIs required for certain browser storage systems. ... -
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Triton
Development repository for the Triton language and compiler
...It aims to bridge the gap between low-level GPU programming, such as CUDA, and higher-level abstractions by providing a more productive and flexible environment for developers. Triton enables users to write optimized kernels for machine learning workloads while maintaining readability and control over performance-critical aspects like memory access patterns and parallel execution. The project leverages LLVM and MLIR to compile code into efficient GPU instructions, supporting both NVIDIA and AMD hardware. It is widely used in research and production environments where custom tensor operations are required, offering both high performance and developer-friendly syntax. -
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Thrive
The main repository for the development of the evolution game Thrive
...Our team seeks to accomplish two major goals: create engaging, compelling gameplay that respects our players’ intelligence, and remain as accurate as possible in our depiction of known scientific theory without compromising the former. Thrive will encapsulate the player in the wonders of science and the universe, allowing them to manipulate the virtual world around them with editors to modify technology, culture, organisms, and entire solar systems. Seven stages are planned, Microbe, Multicellular, Aware, Awakening, Society, Industrial and Space, though for the moment we’re only focusing on the first of these. -
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BotSharp
AI Multi-Agent Framework in .NET
Conversation as a platform (CaaP) is the future, so it's perfect that we're already offering the whole toolkits to our .NET developers using the BotSharp AI BOT Platform Builder to build a CaaP. It opens up as much learning power as possible for your own robots and precisely control every step of the AI processing pipeline. BotSharp is an open source machine learning framework for AI Bot platform builder. This project involves natural language understanding, computer vision and audio processing technologies, and aims to promote the development and application of intelligent robot assistants in information systems. Out-of-the-box machine learning algorithms allow ordinary programmers to develop artificial intelligence applications faster and easier. ... -
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Numba
NumPy aware dynamic Python compiler using LLVM
Numba is an open source JIT compiler that translates a subset of Python and NumPy code into fast machine code. Numba translates Python functions to optimized machine code at runtime using the industry-standard LLVM compiler library. Numba-compiled numerical algorithms in Python can approach the speeds of C or FORTRAN. You don't need to replace the Python interpreter, run a separate compilation step, or even have a C/C++ compiler installed. -
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PyTorch Geometric
Geometric deep learning extension library for PyTorch
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 an easy-to-use mini-batch loader for many small and single giant graphs, a large number of common benchmark datasets (based on simple interfaces to create your own), and helpful transforms, both for learning on arbitrary graphs as well as on 3D meshes or point clouds. We have outsourced a lot of... -
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Google Translate PHP
Free Google Translate API PHP Package
A simple and effective PHP library for translating text using Google Translate without needing an API key. It allows developers to integrate real-time translation features into their applications with minimal setup and supports multiple languages, leveraging Google Translate’s unofficial endpoint. -
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plantuml.jar
PlantUML plugin for Jekyll: helps you embed UML diagrams
PlantUML plugin for Jekyll: helps you embed UML diagrams into static pages. -
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SDGym
Benchmarking synthetic data generation methods
...Select any of the publicly available datasets from the SDV project, or input your own data. Choose from any of the SDV synthesizers and baselines. Or write your own custom machine learning model. In addition to performance and memory usage, you can also measure synthetic data quality and privacy through a variety of metrics. Install SDGym using pip or conda. We recommend using a virtual environment to avoid conflicts with other software on your device. -
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SQLite compiled to JavaScript
A javascript library to run SQLite on the web
sql.js is a javascript SQL database. It allows you to create a relational database and query it entirely in the browser. You can try it in this online demo. It uses a virtual database file stored in memory, and thus doesn't persist the changes made to the database. However, it allows you to import any existing sqlite file, and to export the created database as a JavaScript typed array. sql.js uses emscripten to compile SQLite to webassembly (or to javascript code for compatibility with older browsers). ... -
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WASM-4
Build retro games using WebAssembly for a fantasy console
wasm4 is a WebAssembly-based game console for building and sharing games using WebAssembly. It provides a virtual platform with a defined specification for game development. -
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miso
A tasty Haskell front-end framework
Miso is a small, production-ready, "isomorphic" Haskell front-end framework for quickly building highly interactive single-page web applications. It features a virtual-dom, recursive diffing / patching algorithm, attribute and property normalization, event delegation, event batching, SVG, Server-sent events, Websockets, type-safe servant-style routing and an extensible Subscription-based subsystem. Inspired by Elm, Redux and Bobril. Miso is pure by default, but side effects (like XHR) can be introduced into the system via the Effect data type. ... -
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satellite-image-deep-learning
Resources for deep learning with satellite & aerial imagery
This page lists resources for performing deep learning on satellite imagery. To a lesser extent classical Machine learning (e.g. random forests) are also discussed, as are classical image processing techniques. Note there is a huge volume of academic literature published on these topics, and this repository does not seek to index them all but rather list approachable resources with published code that will benefit both the research and developer communities. -
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PHPStan
Dscover bugs in your code without running it!
...PHPStan scans your whole codebase and looks for both obvious & tricky bugs. Even in those rarely executed if statements that certainly aren't covered by tests. You can run it on your machine and in CI to prevent those bugs ever reaching your customers in production. Thanks to rule levels you don't get overwhelmed with thousands of errors on the first run. You can increase PHPStan's capabilities on your code at your own pace. It makes work feel like a game. It doesn't matter how old your code is, PHPStan is here to help you improve it. ...
