Popular GitHub Repositories for Email 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.

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

HumanLayer enables AI agents to communicate with humans in tool-based and async workflows. Guarantee human oversight of high-stakes function calls with approval workflows across slack, email and more. Bring your LLM and Framework of choice and start giving your AI agents safe access to the world. Agentic Workflows, human in the loop, tool calling

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

Send emails directly from Cursor with this email sending MCP server

Search for anything using Google, DuckDuckGo, phind.com, Contains AI models, can transcribe yt videos, temporary email and phone number generation, has TTS support, webai (terminal gpt and open interpreter) and offline LLMs

Enterprise IM Solution with AI powered live chat, email support, omni-channel customer service & team im，alternative to slack + zendesk/intercom

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

Email clustering with machine learning

AI enabled insights from emails, calendars, contacts, files, Slack, databases, web... Fast, private and local. Launching soon!