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libonnx is a lightweight, portable pure C99 ONNX inference engine for embedded devices with hardware acceleration support. Its .c and .h files can be dropped into a project and compiled with it. Models are loaded from a file into a context, and inference runs on input tensors via onnx_run. It is based on ONNX version v1.17.0 with opset 24 support, and some operators are not implemented.
An MIT OpenCourseWare course covering matrix theory and linear algebra, emphasizing topics useful in physics, economics, social sciences, natural sciences and engineering. It is designed for independent study and includes lecture videos by Gilbert Strang, summary notes, problem solving videos, and problem sets with solutions.
A free downloadable guide from Kolena Inc. on testing large language models. It identifies principles for creating reliable testing protocols and details approaches for measuring model effectiveness in NLP tasks such as text summarization and prompt engineering, and discusses tracking performance differences over time.
Local Deep Research is a tool that achieves approximately 95% accuracy on the SimpleQA benchmark, with an example run using Qwen3.6-27B on an RTX 3090. It supports all local and cloud LLMs including llama.cpp, Ollama, and Google models, integrates over 10 search engines such as arXiv, PubMed, and private document sources, and operates with local and encrypted processing.
LocalAI is described as an open source AI engine that runs models, including LLMs, vision, voice, image and video, on any hardware without a GPU. It presents itself as a drop-in replacement for most upstream APIs and includes a built-in agent platform powered by LocalAGI, whose agents can reason, use tools and maintain memory. Image generation with Stable diffusion on CPU is also supported.
Magic.dev is an artificial intelligence company focused on developing safe artificial general intelligence (AGI) to accelerate progress on high-priority global problems. The company builds frontier code models intended to automate software engineering and AI research workflows. Its technical approach combines large-scale pre-training, domain-specific reinforcement learning, extended context windows, and increased inference-time compute. Magic.dev employs a small team of engineers and researchers working on fundamental AGI-related research problems.
Apache Mahout builds an environment for quickly creating scalable, performant machine learning applications. Its current work centers on quantum machine learning in Python, with Qumat, a high-level library for writing quantum circuits once and running them on supported backends, and QDP, a GPU-accelerated engine that turns classical data into quantum states. The earlier Mahout Classic codebase is in maintenance mode.
Manus is described as an action engine that executes tasks and automates workflows. Its features page lists building web and mobile apps, creating videos, slides and designs, research, and automations. A video feature uses Seedance 2.5 to generate shots, with editable tracks in a Video Editor.
Marblism offers AI employee services to support and scale business operations. Its AI tools are built to handle a range of common business tasks including inbox management, social media management, search engine optimization, lead generation, phone calls, and customer support. The service provides a free starting option for new users to test its features.
Open-source project that provides conversational AI for questions, tasks, and general assistance.
News and Hackathons for AI Engineers!
Metabob is a real-time, intelligent code analysis engine that runs in parallel with generative AI coding tools.
An asynchronous engine for continuous & autonomous machine learning, built for real-time usage.
MLflow is an open source AI engineering platform for agents, LLMs, and ML models. It provides tools for debugging, evaluating, monitoring, and optimizing AI applications, including tracing, evaluation metrics, prompt management, an AI gateway, and an agent server. The project is released under the Apache 2.0 license.
MLOps Community is a global community for machine learning engineers focused on MLOps. It facilitates knowledge sharing, real-world problem solving, networking, and career advancement through in-person meetups and conferences, virtual tech talks, podcasts, workshops, and masterclasses. It reports membership of over 70,000 to 90,000 ML practitioners.
Global, black box optimization engine for real world metric optimization by Yelp.
NNI is an open source AutoML toolkit developed by Microsoft. It automates tasks across the machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning for machine learning workflows.
NobodyWho is an inference engine that runs LLMs locally and offline on any device, powered by llama.cpp. Bindings are available for Kotlin, Swift, React Native, Flutter, Python and Godot. It supports GGUF models, tool calling, multimodal input, text-to-speech and speech-to-text.
An archived, read-only GitHub repository holding an open solution to the Home Credit Default Risk challenge. It provides code, configs and notebooks plus documented solutions using LightGBM, sklearn and XGBoost with engineered features; the README lists cross-validation and leaderboard scores for each. References to Neptune are optional and the solution can run as a plain Python script.
Lobster is an Openclaw-native workflow shell described as a typed, local-first macro engine that turns skills and tools into composable pipelines and automations. Workflows use JSON-first typed pipelines and can include approval and input gates that OpenClaw presents to the user. It requires Node.js 22 or newer and the pnpm version pinned in package.json. Captured process output is unlimited by default unless an output byte limit is set.
OpenLIT is an open-source agent harness engineering platform built on OpenTelemetry. It provides tracing, evaluations, guardrails, prompt and context management, and cost and GPU monitoring for the harness around AI agents and coding agents. It is free to self-host under Apache 2.0 and is described as working with many models, frameworks and harnesses.
Cleansing, pre-processing, feature engineering, exploratory data analysis and easy ML with PySpark backend.
Platform and SDK for AI Engineers providing tools for LLM evaluation, observability, and a version-controlled enhanced prompt playground.
AI-powered answer engine that searches the web and cites sources for research questions.
