Popular GitHub Repositories for Badge Validation

structured outputs for llms

The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.

Evidently is ??an open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. From tabular data to Gen AI. 100+ metrics.

Core ML tools contain supporting tools for Core ML model conversion, editing, and validation.

? Open-Source Evaluation & Testing for AI & LLM systems

Deepchecks: Tests for Continuous Validation of ML Models & Data. Deepchecks is a holistic open-source solution for all of your AI & ML validation needs, enabling to thoroughly test your data and models from research to production.

README file generator, powered by AI.

A high-level machine learning and deep learning library for the PHP language.

Automatically find issues in image datasets and practice data-centric computer vision.

Perception toolkit for sim2real training and validation in Unity

The toolkit to test, validate, and evaluate your models and surface, curate, and prioritize the most valuable data for labeling.

A full pipeline AutoML tool for tabular data

State-of-the art Automated Machine Learning python library for Tabular Data

Workshop (6 hours): preprocessing, cross-validation, lasso, decision trees, random forest, xgboost, superlearner ensembles

? A curated list of papers & technical articles on AI Quality & Safety

A library that unifies the API for most commonly used libraries and modeling techniques for time-series forecasting in the Python ecosystem.

一个可用于生产环境的、基于大型语言模型 (LLM) 的 Node.js 和 TypeScript REST API 模板，重点关注清晰架构。

Apache Liminals goal is to operationalise the machine learning process, allowing data scientists to quickly transition from a successful experiment to an automated pipeline of model training, validation, deployment and inference in production. Liminal provides a Domain Specific Language to build ML workflows on top of Apache Airflow.

An MCP server that securely interfaces with your iMessage database via the Model Context Protocol (MCP), allowing LLMs to query and analyze iMessage conversations. It includes robust phone number validation, attachment processing, contact management, group chat handling, and full support for sending and receiving messages.

?? A production-ready LLM-Powered Node.js & TypeScript REST API template, with a focus on Clean Architecture