Search Results for "machine" - Page 36
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Showing 4715 open source projects for "machine"
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Ultralytics
Ultralytics YOLO
Ultralytics is a comprehensive computer vision framework that provides state-of-the-art implementations of the YOLO (You Only Look Once) family of models, enabling developers to perform tasks such as object detection, segmentation, classification, tracking, and pose estimation within a unified system. It is designed to be fast, accurate, and easy to use, offering both command-line and Python-based interfaces for training, validation, and deployment of machine learning models. The framework supports a full end-to-end workflow, including dataset preparation, model training, evaluation, and export to various deployment formats. Its architecture emphasizes performance optimization, balancing speed and accuracy to support real-time applications across industries. Ultralytics also provides pretrained models and flexible configuration options, allowing users to adapt the system to different datasets and use cases with minimal effort. -
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autoMate
AI tool for automating desktop tasks via natural language input
...Unlike conventional RPA tools that require predefined workflows, autoMate dynamically adapts to tasks by making autonomous decisions based on the current interface state. autoMate emphasizes local execution, meaning all processing happens on the user’s machine to maintain privacy and data security. -
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Google Research
This repository contains code released by Google Research
Google Research is a massive monorepo that hosts a wide range of research code released by Google Research teams across machine learning, artificial intelligence, robotics, natural language processing, and other advanced domains. Rather than being a single framework, the repository serves as a centralized collection of experimental projects, reference implementations, and reproducible research artifacts. It is intended primarily for researchers and advanced practitioners who want to explore cutting-edge techniques directly from the teams that developed them. ... -
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ESPectre
Motion detection system based on Wi-Fi spectre analysis (CSI)
...At its core, it analyzes Wi-Fi Channel State Information (CSI) — detailed measurements of how Wi-Fi waves change as they propagate — to mathematically detect disturbances caused by human movement between a Wi-Fi router and an ESP32 microcontroller, eliminating the need for machine learning or training data to operate effectively. Designed to integrate natively with Home Assistant through ESPHome, ESPectre exposes motion and movement intensity sensors directly to home automation dashboards, allowing users to trigger automations like lighting, heating, or security alerts when motion is detected. -
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mcp-cli
Lighweight CLI to interact with MCP servers
...The Model Context Protocol is an emerging open standard for connecting language models and external tools, and mcp-cli helps mitigate common pain points like context window bloat by dynamically discovering MCP servers and reducing token load during interactions. It’s designed to be fast and shell-friendly, compiling to a single standalone binary and producing machine-readable output (e.g., JSON) that plays well with other CLI tooling like jq and standard piping. mcp-cli supports both stdio and HTTP-based MCP servers, connection pooling with a lazy-spawn daemon to keep connections warm, and flexible tool filtering via easy configuration options. -
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Zarf
DevSecOps for Air Gap & Limited-Connection Systems
Zarf eliminates the complexity of air gap software delivery for Kubernetes clusters and cloud-native workloads using a declarative packaging strategy to support DevSecOps in offline and semi-connected environments. -
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Clash
Haskell to VHDL/Verilog/SystemVerilog compiler
Clash is a functional hardware description language that borrows both its syntax and semantics from the functional programming language Haskell. It provides a familiar structural design approach to both combinational and synchronous sequential circuits. The Clash compiler transforms these high-level descriptions to low-level synthesizable VHDL, Verilog, or SystemVerilog. Clash is an open-source project, licensed under the permissive BSD2 license, and actively maintained by QBayLogic. The... -
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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. ... -
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AI Chatbot Framework
Python chatbot framework with Natural Language Understanding
...You don’t need to be an expert at artificial intelligence to create an awesome chatbot that has AI capabilities. With this boilerplate project you can create an AI-powered chatting machine in no time. -
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GraphEmbedding
Implementation and experiments of graph embedding algorithms
...Users can configure walks, embedding dimensions, training windows, epochs, and other model-specific parameters. Example scripts demonstrate how to train models and retrieve embeddings for downstream graph analysis or machine learning tasks. -
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react-native-fast-tflite
High-performance TensorFlow Lite library for React Native
...The library supports zero-copy ArrayBuffers, which helps reduce overhead when passing model inputs and outputs through React Native. It can load and swap TensorFlow Lite models at runtime, making it useful for apps that run multiple machine learning tasks. The project supports GPU-accelerated delegates such as CoreML, Metal, and OpenGL. It is especially useful for mobile computer vision, on-device inference, and VisionCamera-based workflows that need fast local model execution. -
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docker-host
A docker sidecar container to forward all traffic to local docker host
docker-host is a Docker sidecar container that forwards traffic from containers to the local Docker host or another configured host. It is useful in environments where containers need to reach services running on the host machine, especially when direct host networking is unavailable or inconsistent across platforms. The project creates a predictable network alias, commonly used as docker-host, so other containers can connect through a stable name. It supports TCP and UDP traffic forwarding examples and can be used inside custom Docker networks or Docker Compose setups. ... -
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darwin-skill
Autoresearch-inspired autonomous skill optimization for Claude Code
darwin-skill is an experimental framework designed to automatically improve AI agent “skills” through iterative evaluation and optimization loops inspired by machine learning training processes. Instead of treating prompts or skill definitions as static assets, the system applies a continuous improvement cycle that evaluates performance, proposes changes, tests outcomes, and either retains or reverts modifications. The framework introduces a scoring system across multiple dimensions, enabling quantitative assessment of skill quality and ensuring that only improvements are preserved over time. ... -
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NVIDIA Warp
A Python framework for accelerated simulation, data generation
...Warp provides a set of primitives for working with arrays, geometry, and physics operations, allowing users to implement complex simulations without writing low-level CUDA code directly. It also supports differentiable programming, enabling gradients to be computed through simulation pipelines, which is particularly valuable for machine learning integration. -
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SWIFT LLM
Use PEFT or Full-parameter to CPT/SFT/DPO/GRPO 600+ LLMs
SWIFT LLM is a comprehensive framework developed within the ModelScope ecosystem for training, fine-tuning, evaluating, and deploying large language models and multimodal models. The platform provides a full machine learning pipeline that supports tasks ranging from model pre-training to reinforcement learning alignment techniques. It integrates with popular inference engines such as vLLM and LMDeploy to accelerate deployment and runtime performance. The framework also includes support for many modern training strategies, including preference learning methods and parameter-efficient fine-tuning techniques. ms-swift is designed to work with hundreds of language and multimodal models, providing a unified environment for experimentation and production deployment. -
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Tree
tree is a library for working with nested data structures
...It generalizes Python’s built-in map function to operate over arbitrarily nested collections — including lists, tuples, dicts, and custom container types — while preserving their structure. This makes it particularly useful in machine learning pipelines and JAX-based workflows, where complex parameter trees or hierarchical state representations are common. The library provides efficient operations such as flatten, unflatten, and map_structure, enabling users to apply functions to all leaves of a nested structure seamlessly. Backed by a high-performance C++ core, tree is optimized for large-scale, performance-critical applications. -
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sparklyr
R interface for Apache Spark
sparklyr is an R package that provides seamless interfacing with Apache Spark clusters—either local or remote—while letting users write code in familiar R paradigms. It supplies a dplyr-compatible backend, Spark machine learning pipelines, SQL integration, and I/O utilities to manipulate and analyze large datasets distributed across cluster environments. -
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Dask
Parallel computing with task scheduling
...It integrates with familiar tools like NumPy, Pandas, and scikit-learn while enabling execution across cores or nodes with minimal code changes. Dask excels at handling large datasets that don’t fit into memory and is widely used in data science, machine learning, and big data pipelines. -
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Kalavai
Turn everyday devices into your own AI cluster
Kalavai is a self-hosted platform that turns everyday devices into your very own AI cluster. Do you have an old desktop or a gaming laptop gathering dust? Aggregate resources from multiple machines and say goodbye to CUDA out-of-memory errors. Deploy your favorite open-source LLM, fine-tune it with your own data, or simply run your distributed work, zero-DevOps. Simple. Private. Yours. -
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Robusta KRR
Prometheus-based Kubernetes Resource Recommendations
Robusta KRR (Kubernetes Resource Recommender) is a CLI tool for optimizing resource allocation in Kubernetes clusters. It gathers pod usage data from Prometheus and recommends requests and limits for CPU and memory. This reduces costs and improves performance. -
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Tetragon
eBPF-based Security Observability and Runtime Enforcement
Tetragon is a flexible Kubernetes-aware security observability and runtime enforcement tool that applies policy and filtering directly with eBPF, allowing for reduced observation overhead, tracking of any process, and real-time enforcement of policies. Observe the complete lifecycle of every process on your machine with Kubernetes context awareness. Translate high-level policies for file monitoring, network observability, container security, and more into low-overhead eBPF programs. Synchronous monitoring, filtering, and enforcement completely in the kernel with eBPF. -
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SciMLBase.jl
The Base interface of the SciML ecosystem
...The SciML common interface ties together the numerical solvers of the Julia package ecosystem into a single unified interface. It is designed for maximal efficiency and parallelism, while incorporating essential features for large-scale scientific machine learning such as differentiability, composability, and sparsity. -
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quick-xml
Rust high performance xml reader and writer
High-performance xml pull reader/writer. The reader is almost zero-copy (use of Cow whenever possible) It is easy on memory allocation (the API provides a way to reuse buffers) It supports various encoding (with encoding feature), namespaces resolution, and special characters. Syntax is inspired by xml-rs. When using the serialize feature, quick-xml can be used with serde's Serialize/Deserialize traits. The mapping between XML and Rust types, and in particular the syntax that allows you to... -
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HUSTOJ
Popular Open Source Online Judge based on PHP/C++/MySQL/Linux
...(Only the original part of the code, which uses components from other open-source projects, please follow the agreement of the original component.) Because the web terminal/database/judgment machine are all packaged in the same image and cannot be extended, it is not recommended to use this image for distributed judgment. In addition, please do not use the SHM file system in Docker, it will be unable to mount due to insufficient memory space The sandbox environment causes inexplicable runtime errors. The default location of script installation is /home/judge, where src is all source code, data is test data, etc directory is the configuration file of the judgment side, and the install directory is various tool scripts. -
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FinMind
Open Data, more than 50 financial data
...Regardless of the program, you can download data through the api provided by FinMind, or you can download data directly from the website. After data is available, statistical analysis, regression analysis, time series analysis, machine learning, and deep learning can be performed. For individual stocks, provide visual analysis of technical, fundamental, and chip levels. According to different strategies, back-test analysis is performed to provide performance, profit and loss, and stock selection targets of different strategy investment portfolios.
