GitHub-проекты

A fast out-of-core learning system.

The Shogun Machine Learning Toolbox.

An open-source, low-code machine learning library in Python that automates machine learning workflows.

A general-purpose network embedding framework: pair-wise representations optimization Network Edit.

A general-purpose library with C/C++ interface for Bayesian data analysis and visualization via serial/parallel Monte Carlo and MCMC simulations. Documentation can be found here.

Open source AI infrastructure layer. Eight agents run automatically: security, caching, memory, hallucination detection, and tamper-proof audit trail. Runs locally.

An open-source cross-platform performance library for deep learning applications.

CEA-List's CAD framework for designing and simulating Deep Neural Network, and building full DNN-based applications on embedded platforms

Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Go, JavaScript and more.

A production-ready library for multicalibration, fairness, and bias correction in machine learning models.

A generic approach that allows to mimic most factorization models by feature engineering.

Microsoft's fast, distributed, high performance gradient boosting (GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.

A high performance software library developed by Intel and optimized for Intel's architectures. Library provides algorithmic building blocks for all stages of data analytics and allows to process data in batch, online and distributed modes.

Easy-to-use and flexible AutoML library for Python.

A highly-modular C++ machine learning library for embedded electronics and robotics.

A dynamic neural network library working well with networks that have dynamic structures that change for every training instance. Written in C++ with bindings in Python.

A software library created by Amazon for training and deploying deep neural networks using GPUs which emphasizes speed and scale over experimental flexibility.

A machine learning API and server written in C++11. It makes state of the art machine learning easy to work with and integrate into existing applications.

The Computational Network Toolkit (CNTK) by Microsoft Research, is a unified deep-learning toolkit that describes neural networks as a series of computational steps via a directed graph.

General purpose gradient boosting on decision trees library with categorical features support out of the box. It is easy to install, contains fast inference implementation and supports CPU and GPU (even multi-GPU) computation.

A deep learning framework developed with cleanliness, readability, and speed in mind. [DEEP LEARNING]

A simple Multi-armed Bandit library. [Deprecated]

A real-time multi-person keypoint detection library for body, face, hands, and foot estimation

VIGRA is a genertic cross-platform C++ computer vision and machine learning library for volumes of arbitrary dimensionality with Python bindings.

A C++ edge video AI engine for RTSP ingestion, CV/VLM inference, visual pipeline orchestration, alarms, and event delivery on Sophon and Rockchip NPUs.

On-device streaming speech recognition runtime with C API for Linux (aarch64/x8664). Based on NVIDIA NeMo FastConformer (80 ms cache-aware lookahead). Companion Silero VAD, wake-word, and 14-command KWS via same runtime.

Ultralytics' YOLOv8 implementation with C++ support for real-time object detection and tracking, optimized for edge devices.

C-based/Cached/Core Computer Vision Library, A Modern Computer Vision Library.

A native C CPU inference engine for running the 284B-A13B DeepSeek-V4-Flash-0731 on one laptop, reaching up to 1.12 token/s on tested hardware while streaming the 167 GB checkpoint from disk with a tested 8 GB memory path and no GPU or Python.

A native C inference engine for running Qwen3.8-27B locally on a single laptop CPU, with direct GGUF loading and a tested 8 GB memory path.

Neural networks framework in pure C: training and inference, no dependencies.

A lightweight C library for ONNX model inference, optimized for performance and portability across platforms.

A lightweight, portable pure C99 onnx inference engine for embedded devices with hardware acceleration support.

An ONNX runtime written in pure C (99) with zero dependencies focused on small embedded devices. Run inference on your machine learning models no matter which framework you train it with. Easy to install and compiles everywhere, even in very old devices.

neonrvm is an open source machine learning library based on RVM technique. It's written in C programming language and comes with Python programming language bindings.

A hybrid recommender system based upon scikit-learn algorithms. [Deprecated]

A C library for product recommendations/suggestions using collaborative filtering (CF).

Darknet is an open source neural network framework written in C and CUDA. It is fast, easy to install, and supports CPU and GPU computation.

Naive Bayesian Classifier implementation in APL. [Deprecated]

MCP server for accessing and managing Kibana dashboards, visualizations, and index patterns through natural language.

🚀 ☁️ - An MCP server application that sends various types of messages to the WeCom group robot.

🎖️ ☁️ - Trade stocks and crypto on common brokerages (Robinhood, ETrade, Coinbase, Kraken) via Trade Agent's MCP server.

The Fastest Gower Distance Implementation for Python. GPU-accelerated similarity matching for mixed data types, 15-25% faster than alternatives with production-ready reliability.

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gpt-computer-assistant

github.com

dockerized mcp client with Anthropic, OpenAI and Langchain.

AI-assisted reminiscence therapy for elderly cognitive training. Narrative quality scoring (v0.7), life story book generation. Chinese + English.