Search Results for "machine" - Page 15
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Showing 4715 open source projects for "machine"
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MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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One Monitoring Tool for IT, OT and Cloud | Free TrialModern infrastructure spans data centers, cloud platforms and factory floors, and every blind spot between them is a risk. PRTG supports SNMP, WMI, SSH and other standard protocols to monitor IT, OT and hybrid environments through one customizable dashboard. Build the views your team needs, from network health to application performance, without switching tools. Try PRTG free for 30 days now.
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chezmoi
Manage your dotfiles across multiple diverse machines, securely
Manage your dotfiles across multiple diverse machines, securely. chezmoi helps you manage your personal configuration files (dotfiles, like ~/.gitconfig) across multiple machines. chezmoi provides many features beyond symlinking or using a bare git repo including templates (to handle small differences between machines), password manager support (to store your secrets securely), importing files from archives (great for shell and editor plugins), full file encryption (using gpg or age), and running scripts (to handle everything else). chezmoi is helpful if you have spent time customizing the tools you use (e.g. shells, editors, and version control systems) and want to keep machines running different accounts (e.g. home and work) and/or different operating systems (e.g. Linux, macOS, and Windows) in sync, while still being able to easily cope with differences from machine to machine. -
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Recommenders
Best practices on recommendation systems
...Implementations of several state-of-the-art algorithms are included for self-study and customization in your own applications. Please see the setup guide for more details on setting up your machine locally, on a data science virtual machine (DSVM) or on Azure Databricks. Independent or incubating algorithms and utilities are candidates for the contrib folder. This will house contributions which may not easily fit into the core repository or need time to refactor or mature the code and add necessary tests. -
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The Powder Toy
Sandbox video game with a powerful physics engine
...The game provides you with various building materials, liquids, gases and electronic components which can be used to construct complex machines, guns, bombs, realistic terrains and almost anything else. You can then mine them and watch cool explosions, add intricate wirings, play with little stickmen or operate your machine. You can browse and play thousands of different saves made by the community or upload your own -
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Concat
Open-Source CapCut replacement (MCP supported)
Concat is a free and open-source desktop video editor positioned as a local alternative to subscription-based editors such as CapCut. It uses a native Rust engine and performs editing entirely on the user’s machine. Projects can contain multiple tracks and timelines for more complex compositions. Core editing tools include splitting, trimming, merging, transitions, and playback-speed adjustment. Offline features include automatic captions, local text-to-speech voices, voice processing, titles, and styled text. Templates allow reusable edit structures to be applied across projects. ... -
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Coinbase Agentic Wallet Skills
npx skills add coinbase/agentic-wallet-skills
...The architecture is centered on composability, where each skill represents a discrete capability such as sending stablecoins, trading tokens, or interacting with paid APIs. It also leverages the x402 protocol, which enables machine-to-machine payments and autonomous service consumption. -
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Weights and Biases
Tool for visualizing and tracking your machine learning experiments
Use W&B to build better models faster. Track and visualize all the pieces of your machine learning pipeline, from datasets to production models. Quickly identify model regressions. Use W&B to visualize results in real time, all in a central dashboard. Focus on the interesting ML. Spend less time manually tracking results in spreadsheets and text files. Capture dataset versions with W&B Artifacts to identify how changing data affects your resulting models. -
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FIT Framework
An enterprise-level AI development framework
...It supports experimentation with different models and datasets, allowing developers to iterate quickly while maintaining clear organization of results and configurations. The system is built to be extensible, enabling integration with various machine learning libraries and tools, as well as customization for domain-specific tasks. -
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Book4_Power-of-Matrix
Book_4_Matrix Power | The Iris Book: From Addition, Subtraction
...The repository is continuously updated and intended to accompany the broader Visualize-ML learning ecosystem. Overall, it serves as a visually driven mathematical foundation for students preparing for data science and machine learning work. -
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LRSLibrary
Low-Rank and Sparse Tools for Background Modeling and Subtraction
...Compatibility across MATLAB versions (tested in R2014–R2017) The library includes matrix and tensor methods (over 100 algorithms) and has been tested across MATLAB versions from R2014 onward. The algorithms can also be adapted to other computer vision or machine learning problems beyond video. Large algorithm collection: > 100 matrix- and tensor-based low-rank + sparse methods. Open-source license, documentation and references included. -
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PaddlePaddle
PArallel Distributed Deep LEarning: Machine Learning Framework
PaddlePaddle is an open source deep learning industrial platform with advanced technologies and a rich set of features that make innovation and application of deep learning easier. It is the only independent R&D deep learning platform in China, and has been widely adopted in various sectors including manufacturing, agriculture and enterprise service. PaddlePaddle covers core deep learning frameworks, basic model libraries, end-to-end development kits and more, with support for both... -
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Open CoDesign
Open-source Claude Design alternative
Open CoDesign is an open-source, desktop AI design tool that transforms natural language prompts into fully structured design artifacts such as prototypes, slide decks, and marketing assets. It is designed as a local-first alternative to cloud-based design tools, allowing users to run everything on their own machine while bringing their own AI model and API keys. The system supports multiple model providers and integrates directly with existing developer tools, enabling seamless workflows without vendor lock-in. It generates HTML, React components, PDFs, and other outputs in real time, rendered in a sandboxed preview environment. The architecture emphasizes privacy, with all data stored locally and no mandatory accounts or telemetry. ... -
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Public APIs
A collective list of free APIs
...Curated by community contributors and the team at APILayer, it serves as a centralized resource for discovering APIs across a wide range of domains, including data, machine learning, weather, entertainment, and finance. The project aims to make API exploration and integration more accessible by offering a single, organized index of open and free-to-use APIs. Developers can leverage this list to enhance their products, prototypes, or research projects without the need to build data sources from scratch. ... -
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PyG
Graph Neural Network Library for PyTorch
PyG (PyTorch Geometric) is a library built upon PyTorch to easily write and train Graph Neural Networks (GNNs) for a wide range of applications related to structured data. 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 easy-to-use mini-batch loaders for operating on many small and single giant graphs, multi GPU-support, DataPipe support,... -
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supabase-py
Python Client for Supabase. Query Postgres from Flask, Django
Python Client for Supabase. Query Postgres from Flask, Django, FastAPI. Python user authentication, security policies, edge functions, file storage, and realtime data streaming. Good first issue. -
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PySyft
Data science on data without acquiring a copy
Most software libraries let you compute over the information you own and see inside of machines you control. However, this means that you cannot compute on information without first obtaining (at least partial) ownership of that information. It also means that you cannot compute using machines without first obtaining control over those machines. This is very limiting to human collaboration and systematically drives the centralization of data, because you cannot work with a bunch of data... -
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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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Voicebox
The open-source voice synthesis studio powered by Qwen3-TTS
Voicebox is a local-first voice synthesis studio that aims to bring professional, DAW-like voice generation workflows to a desktop app while keeping models and voice data entirely on your machine. It positions itself as an open-source alternative to cloud voice platforms by emphasizing privacy, offline use, and freedom from subscriptions or usage caps. The tool supports downloading voice models, cloning voices from short audio samples, and generating speech locally, then organizing the results using studio-oriented editing concepts. ... -
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Hummingbird
Hummingbird compiles trained ML models into tensor computation
Hummingbird is a library for compiling trained traditional ML models into tensor computations. Hummingbird allows users to seamlessly leverage neural network frameworks (such as PyTorch) to accelerate traditional ML models. Thanks to Hummingbird, users can benefit from (1) all the current and future optimizations implemented in neural network frameworks; (2) native hardware acceleration; (3) having a unique platform to support both traditional and neural network models; and having all of... -
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Cortex
A horizontally scalable, multi-tenant, long term Prometheus
Horizontally scalable, highly available, multi-tenant, long-term storage for Prometheus. Durably store data for longer than the lifetime of any single machine, and use this data for long-term capacity planning. Cortex makes your PromQL queries blazin' fast through aggressive parallelization and caching. Cortex gives you a global view of Prometheus time series data that includes data in long-term storage, greatly expanding the usefulness of PromQL for analytical purposes. Cortex runs across multiple machines in a cluster, exceeding the throughput and storage of a single machine. ... -
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AlphaZero.jl
A generic, simple and fast implementation of Deepmind's AlphaZero
Beyond its much publicized success in attaining superhuman level at games such as Chess and Go, DeepMind's AlphaZero algorithm illustrates a more general methodology of combining learning and search to explore large combinatorial spaces effectively. We believe that this methodology can have exciting applications in many different research areas. Because AlphaZero is resource-hungry, successful open-source implementations (such as Leela Zero) are written in low-level languages (such as C++)... -
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Denoising Diffusion Probabilistic Model
Implementation of Denoising Diffusion Probabilistic Model in Pytorch
Implementation of Denoising Diffusion Probabilistic Model in Pytorch. It is a new approach to generative modeling that may have the potential to rival GANs. It uses denoising score matching to estimate the gradient of the data distribution, followed by Langevin sampling to sample from the true distribution. If you simply want to pass in a folder name and the desired image dimensions, you can use the Trainer class to easily train a model. -
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LiteRT-LM
LiteRT-LM is Google's production-ready inference framework
LiteRT-LM is Google’s open-source inference framework for deploying large language models on edge devices. It is built for production-oriented local LLM execution across Android, iOS, desktop, web, embedded, and IoT environments. The framework focuses on performance, hardware acceleration, and efficient model serving close to the user instead of relying only on remote cloud inference. It supports CPU execution across major platforms and adds GPU or NPU acceleration where available. LiteRT-LM... -
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PCjs Machines
The original IBM PC and other machine emulations in JavaScript
PCjs Machines is a browser-based emulation platform that recreates a wide range of early computing systems, including the original IBM PC and other historical machines, entirely using JavaScript. It serves both as an emulator and a digital preservation project, allowing users to interact with vintage software and hardware environments directly in their web browsers. The platform includes support for multiple architectures such as x86, 6502, and 8080-based systems, as well as minicomputers... -
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deepjazz
Deep learning driven jazz generation using Keras & Theano
deepjazz is a deep learning project that generates jazz music using recurrent neural networks trained on MIDI files. The repository demonstrates how machine learning can learn musical structure and produce original compositions. It uses the Keras and Theano libraries to build a two-layer Long Short-Term Memory network capable of learning temporal patterns in music. The system analyzes musical sequences from an input MIDI file and then generates new musical notes that follow similar stylistic patterns. ... -
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AIGC-Interview-Book
AIGC algorithm engineer interview secrets
...Topics included in the repository span large language models, generative AI systems, traditional deep learning methods, reinforcement learning, computer vision, natural language processing, and machine learning theory. In addition to technical concepts, the repository also contains interview preparation materials such as practice questions, hiring insights, and career advice for AI engineers. The materials are organized so readers can study fundamental topics as well as advanced research areas that frequently appear in technical interviews.
