MLOps2014
Apache Software Foundation, Maxime Beauchemin (originated at Airbnb)Apache Software Foundation, Airbnb
Programmatically author, schedule, and monitor data workflows as Python-defined DAGs; the scheduler handles dependencies, retries, and backfills. Pluggable executors (Local, Celery, Kubernetes) and a broad provider ecosystem for AWS, GCP, and databases.
AI Others2015
Processes and indexes seized digital evidence — disk images, files, timelines — for forensic examiners. Bundles high-speed carving, OCR, named-entity recognition, similar-image and face search, and audio transcription behind scriptable Java parsers.
AI Others2015
Curated collection of AI courses, books, video lectures, papers and engineering guides for developers building generative models and agentic systems. Actively maintained with a weekly, evidence-backed curation workflow and an opinionated quality bar.
AI Infra2015
Exposes auto-generated REST and GraphQL APIs from visual content models so teams can self-host a headless CMS and manage content via a customizable admin UI. Provides a plugin system, TypeScript support, multiple database options, and optional Strapi Cloud hosting.
Readable, minimal-dependency Python implementations of core robotics algorithms — localization (EKF, particle filter), SLAM (ICP, FastSLAM), path planning (A*, RRT*, PRM), and path tracking (LQR, MPC) — written to be studied, not just run.
AI Train2016
Trains gradient-boosted decision trees for classification, ranking, and large-scale tabular ML with lower memory use and faster training. GOSS and EFB help it handle high-dimensional sparse data on CPU, GPU, and distributed setups.
AI Infra2016
Unified Node.js library for web crawling and browser automation that fetches pages and files via headless browsers or raw HTTP. Provides persistent queues, proxy rotation, session management, storage, and human-like fingerprints to build scalable data pipelines (e.g., RAG/LLM datasets).
AI Others2017
Interactive, community-driven learning roadmaps and guides that map skills, technologies, and curated resources for developer career paths — covering frontend, backend, DevOps, ML/AI, MLOps, prompt engineering and more. Clickable nodes link to tutorials, best practices and question banks to guide study and hiring prep.
AI Train2017
Trains gradient-boosted decision trees with native categorical-feature handling, GPU acceleration, and production-ready prediction APIs. A strong fit for tabular ML when preprocessing categories into numeric features would add noise or leakage.
AI Infra2017
Manages polyglot monorepos by caching unchanged outputs and running only affected tasks. Built with Rust and extensible in TypeScript; includes integrated CI features (remote caching, task distribution) and AI-native tooling such as a CLI optimized for autonomous agents and self-healing CI.
AI Infra2017
Provides reusable PyTorch modules and utilities to build, train and scale Graph Neural Networks — includes many implemented GNN layers, benchmark datasets, minibatch/sampling loaders, and support for large-scale, heterogeneous, temporal and point-cloud graphs.