Popular GitHub Repositories for Field Dataset

Qlib is an AI-oriented quantitative investment platform that aims to realize the potential, empower research, and create value using AI technologies in quantitative investment, from exploring ideas to implementing productions. Qlib supports diverse machine learning modeling paradigms. including supervised learning, market dynamics modeling, and RL.

Original reference implementation of "3D Gaussian Splatting for Real-Time Radiance Field Rendering"

pix2tex: Using a ViT to convert images of equations into LaTeX code.

Annotate better with CVAT, the industry-leading data engine for machine learning. Used and trusted by teams at any scale, for data of any scale.

Open source annotation tool for machine learning practitioners.

大规模中文自然语言处理语料 Large Scale Chinese Corpus for NLP

Techniques for deep learning with satellite & aerial imagery

Amphion (/?m?fa??n/) is a toolkit for Audio, Music, and Speech Generation. Its purpose is to support reproducible research and help junior researchers and engineers get started in the field of audio, music, and speech generation research and development.

BISHENG is an open LLM devops platform for next generation Enterprise AI applications. Powerful and comprehensive features include: GenAI workflow, RAG, Agent, Unified model management, Evaluation, SFT, Dataset Management, Enterprise-level System Management, Observability and more.

A powerful tool for creating fine-tuning datasets for LLM

Curated list of Machine Learning, NLP, Vision, Recommender Systems Project Ideas

Detailed and tailored guide for undergraduate students or anybody want to dig deep into the field of AI with solid foundation.

A Collection of Variational Autoencoders (VAE) in PyTorch.

Awesome Pretrained Chinese NLP Models，高质量中文预训练模型&大模型&多模态模型&大语言模型集合

Pytorch implementation for Semantic Segmentation/Scene Parsing on MIT ADE20K dataset

Easily train your own text-generating neural network of any size and complexity on any text dataset with a few lines of code.

A complete guide to start and improve in machine learning (ML), artificial intelligence (AI) in 2025 without ANY background in the field and stay up-to-date with the latest news and state-of-the-art techniques!

Data processing for and with foundation models! ? ? ? ?? ??? ? ?

The project is an official implementation of our CVPR2019 paper "Deep High-Resolution Representation Learning for Human Pose Estimation"

The easiest tool for fine-tuning LLM models, synthetic data generation, and collaborating on datasets.