Popular GitHub Repositories for Quality Assessment

Learn how to design, develop, deploy and iterate on production-grade ML applications.

? Papers & tech blogs by companies sharing their work on data science & machine learning in production.

Composio equip's your AI agents & LLMs with 100+ high-quality integrations via function calling

This repository is primarily maintained by Omar Santos (@santosomar) and includes thousands of resources related to ethical hacking, bug bounties, digital forensics and incident response (DFIR), artificial intelligence security, vulnerability research, exploit development, reverse engineering, and more.

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

Build high-quality LLM apps - from prototyping, testing to production deployment and monitoring.

PyTorch implementation of the U-Net for image semantic segmentation with high quality images

Refine high-quality datasets and visual AI models

High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)

High-quality multi-lingual text-to-speech library by MyShell.ai. Support English, Spanish, French, Chinese, Japanese and Korean.

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.

The Open Source Feature Store for AI/ML

VideoCrafter2: Overcoming Data Limitations for High-Quality Video Diffusion Models

A distributed approximate nearest neighborhood search (ANN) library which provides a high quality vector index build, search and distributed online serving toolkits for large scale vector search scenario.

the LLM vulnerability scanner

Argilla is a collaboration tool for AI engineers and domain experts to build high-quality datasets

MuseTalk: Real-Time High Quality Lip Synchorization with Latent Space Inpainting

Pre-trained Deep Learning models and demos (high quality and extremely fast)

StarVector is a foundation model for SVG generation that transforms vectorization into a code generation task. Using a vision-language modeling architecture, StarVector processes both visual and textual inputs to produce high-quality SVG code with remarkable precision.

Learn how to design, develop, deploy and iterate on production-grade ML applications.