Popular GitHub Repositories for Dataset Augmentation

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.

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

Image augmentation for machine learning experiments.

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

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

A Collection of Variational Autoencoders (VAE) in PyTorch.

A system for quickly generating training data with weak supervision

A GPU-accelerated library containing highly optimized building blocks and an execution engine for data processing to accelerate deep learning training and inference applications.

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

Keras model to generate HTML code from hand-drawn website mockups. Implements an image captioning architecture to drawn source images.

Image augmentation library in Python for machine learning.

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.

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

Data augmentation for NLP