Search Results for "machine" - Page 28
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Showing 4715 open source projects for "machine"
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1
DeepDetect
Deep Learning API and Server in C++14 support for Caffe, PyTorch
The core idea is to remove the error sources and difficulties of Deep Learning applications by providing a safe haven of commoditized practices, all available as a single core. While the Open Source Deep Learning Server is the core element, with REST API, and multi-platform support that allows training & inference everywhere, the Deep Learning Platform allows higher level management for training neural network models and using them as if they were simple code snippets. Ready for applications... -
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NVIDIA NeMo
Toolkit for conversational AI
NVIDIA NeMo, part of the NVIDIA AI platform, is a toolkit for building new state-of-the-art conversational AI models. NeMo has separate collections for Automatic Speech Recognition (ASR), Natural Language Processing (NLP), and Text-to-Speech (TTS) models. Each collection consists of prebuilt modules that include everything needed to train on your data. Every module can easily be customized, extended, and composed to create new conversational AI model architectures. Conversational AI... -
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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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Datasets
Hub of ready-to-use datasets for ML models
Datasets is a library for easily accessing and sharing datasets, and evaluation metrics for Natural Language Processing (NLP), computer vision, and audio tasks. Load a dataset in a single line of code, and use our powerful data processing methods to quickly get your dataset ready for training in a deep learning model. Backed by the Apache Arrow format, process large datasets with zero-copy reads without any memory constraints for optimal speed and efficiency. We also feature a deep... -
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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5
Akka
Build concurrent, distributed, and resilient message-driven apps
...Building on the principles of The Reactive Manifesto Akka allows you to write systems that self-heal and stay responsive in the face of failures. Up to 50 million msg/sec on a single machine. Small memory footprint; ~2.5 million actors per GB of heap. Distributed systems without single points of failure. Load balancing and adaptive routing across nodes. Event Sourcing and CQRS with Cluster Sharding. Distributed Data for eventual consistency using CRDTs. Asynchronous non-blocking stream processing with backpressure. -
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fastai
Deep learning library
fastai is a deep learning library which provides practitioners with high-level components that can quickly and easily provide state-of-the-art results in standard deep learning domains, and provides researchers with low-level components that can be mixed and matched to build new approaches. It aims to do both things without substantial compromises in ease of use, flexibility, or performance. This is possible thanks to a carefully layered architecture, which expresses common underlying... -
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Objeck
Objeck is a modern object-oriented programming language
...Libraries can be linked into executables by passing the names of libraries to the compiler. Objeck can be built for a variety of targets. The language is implemented in C++, assembly (i.e., generated machine code) and assisted by code generators for bindings to SDL2 and GTK 3/4. -
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MicroPython
Python implementation for microcontrollers and constrained systems
MicroPython is a lean and efficient implementation of the Python 3 programming language that includes a small subset of the Python standard library and is optimised to run on microcontrollers and in constrained environments. The MicroPython pyboard is a compact electronic circuit board that runs MicroPython on the bare metal, giving you a low-level Python operating system that can be used to control all kinds of electronic projects. MicroPython is packed full of advanced features such as an... -
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Apache OpenNLP
Apache OpenNLP
Apache OpenNLP is a machine learning-based NLP library that provides tools for text-processing tasks such as tokenization, sentence segmentation, and named entity recognition. -
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img2dataset
Easily turn large sets of image urls to an image dataset
Easily turn large sets of image urls to an image dataset. Can download, resize and package 100M urls in 20h on one machine. Also supports saving captions for url+caption datasets. Opt-out directives: Websites can pass the http headers X-Robots-Tag: noai, X-Robots-Tag: noindex , X-Robots-Tag: noimageai and X-Robots-Tag: noimageindex By default img2dataset will ignore images with such headers. -
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Aeron
Efficient UDP unicast, UDP multicast, and IPC message transport
...Java and C++ clients are available in this repository, and a .NET client is available from a 3rd party. All three clients can exchange messages across machines, or on the same machine via IPC, very efficiently. Message streams can be recorded by the Archive module to persistent storage for later, or real-time, replay. Aeron Cluster provides support for fault-tolerant services as replicated state machines based on the Raft consensus algorithm. Performance is the key focus. A design goal for Aeron is to be the highest throughput with the lowest and most predictable latency of any messaging system. ... -
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Photoshot
An open-source AI avatar generator web app
Photoshot is an AI-powered image generation and editing tool that enables users to create and modify images using advanced machine learning techniques. It allows users to generate realistic portraits, edit existing photos, and apply AI-based enhancements with minimal manual effort. -
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CImGui
Julia wrapper for cimgui
This package provides a Julia language wrapper for cimgui: a thin c-api wrapper programmatically generated for the excellent C++ immediate mode gui Dear ImGui. Dear ImGui is mainly for creating content creation tools and visualization / debug tools. You could browse Gallery to get an idea of its use cases. -
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Open Interpreter
A natural language interface for computers
...It prompts you to approve code before executing, and supports both online LLM models and local inference servers. It seeks to combine convenience (like ChatGPT’s code interpreter) with control and flexibility by running on your own machine. -
15
The Algorithms Python
All Algorithms implemented in Python
...Each implementation is designed with clarity in mind, favoring readability and comprehension over performance optimization. The project covers various domains including mathematics, cryptography, machine learning, sorting, graph theory, and more. With contributions from a large global community, it continually grows and improves through collaboration and peer review. This repository is an ideal reference for students, educators, and developers seeking hands-on experience with algorithmic concepts in Python. -
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OpenRPA
Free Open Source Enterprise Grade RPA
...It is recommended to install it universally (requires administrator previleges), as it have no downsides, so unless something (or someone) prohibits you from installing it for all users, always do it so. Installing OpenRPA single-user prevents other regular users from the machine from using OpenRPA. -
17
x402
A payments protocol for the internet. Built on HTTP
...The protocol supports multiple payment networks, including blockchain-based systems and fiat-compatible facilitators, making it flexible and network-agnostic. It is particularly suited for machine-to-machine transactions, such as AI agents paying for APIs, data, or compute resources without human intervention. The system eliminates the need for accounts, sessions, or traditional payment rails by using cryptographic authorization and wallet-based transactions. Developers can integrate payment requirements into endpoints with minimal code using middleware and SDKs. ... -
18
wacli
WhatsApp CLI
...Beyond basic messaging, it also includes tools for backfilling older history on a best-effort basis, downloading media, and managing groups. The overall design emphasizes human-readable terminal output by default, with optional JSON output for scripting and machine-readable pipelines. -
19
ort
Fast ML inference & training for ONNX models in Rust
ort is a high-performance Rust library that provides bindings to ONNX Runtime, enabling developers to run machine learning inference and training workflows directly within Rust applications using the standardized ONNX model format. It is designed to bridge the gap between modern machine learning frameworks and systems programming by offering a safe, ergonomic API for executing models originally built in ecosystems like PyTorch, TensorFlow, or scikit-learn. -
20
TimeMixer
Decomposable Multiscale Mixing for Time Series Forecasting
TimeMixer is a deep learning framework designed for advanced time series forecasting and analysis using a multiscale neural architecture. The model focuses on decomposing time series data into multiple temporal scales in order to capture both short-term seasonal patterns and long-term trends. Instead of relying on traditional recurrent or transformer-based architectures, TimeMixer is implemented as a fully multilayer perceptron–based model that performs temporal mixing across different... -
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Diffusion for World Modeling
Learning agent trained in a diffusion world model
Diffusion for World Modeling is an experimental reinforcement learning system that trains intelligent agents inside a simulated environment generated by a diffusion-based world model. The project introduces the idea of using diffusion models, commonly used for image generation, to simulate the dynamics of an environment and predict future states based on previous observations and actions. Instead of interacting directly with a real environment, the reinforcement learning agent learns within... -
22
Text2Code for Jupyter notebook
A proof-of-concept jupyter extension which converts english queries
Text2Code for Jupyter notebook project is a proof-of-concept extension for Jupyter Notebook that allows users to generate Python code directly from natural language queries written in English. The tool is designed to simplify data analysis workflows by enabling users to describe their intended operation in plain language instead of manually writing code. When a user enters a textual command, the extension interprets the request and generates a corresponding Python code snippet that can be... -
23
MLE-bench
AI multi-agent framework for automating data-driven R&D workflows
...By iterating through these stages, the framework continuously refines models and strategies using feedback from previous results. RD-Agent focuses heavily on automating complex tasks such as feature engineering, model design, and experimentation, which are traditionally time-consuming in machine learning and quantitative research workflows. RD-Agent can analyze data, generate experimental code, run evaluations, and learn from outcomes to improve future iterations. -
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Semantra
Multi-tool for semantic search
Semantra is an open-source semantic search tool designed to help users explore large collections of documents by meaning rather than simple keyword matching. The software analyzes text and PDF documents stored locally and creates embeddings that allow queries to retrieve results based on conceptual similarity. It is primarily intended for individuals who need to extract insights from large document collections, including researchers, journalists, students, and historians. The system runs... -
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FlexLLMGen
Running large language models on a single GPU
FlexLLMGen is an open-source inference engine designed to run large language models efficiently on limited hardware resources such as a single GPU. The system focuses on high-throughput generation workloads where large batches of text must be processed quickly, such as large-scale data extraction or document analysis tasks. Instead of requiring expensive multi-GPU systems, the framework uses techniques such as memory offloading, compression, and optimized batching to run large models on...
