Stars
The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.
⏩ Create, share, and use custom AI code assistants with our open-source IDE extensions and hub of models, rules, prompts, docs, and other building blocks
Import unstructured data (text and images) into structured tables
Kickstart your MLOps initiative with a flexible, robust, and productive Python package.
Learn how to design, develop, deploy and iterate on production-grade ML applications.
A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
Machine Learning for Imbalanced Data, published by Packt
Code AI platform with Code Search & Cody
Business intelligence as code: build fast, interactive data visualizations in SQL and markdown
SAM-PT: Extending SAM to zero-shot video segmentation with point-based tracking.
Source for https://fullstackdeeplearning.com
Recommendations at "Reasonable Scale": joining dataOps with recSys through dbt, Merlin and Metaflow
YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
📝 An awesome Data Science repository to learn and apply for real world problems.
FashionCLIP is a CLIP-like model fine-tuned for the fashion domain.
💫 Industrial-strength Natural Language Processing (NLP) in Python
🦘 Explore multimedia datasets at scale
Beyond the Imitation Game collaborative benchmark for measuring and extrapolating the capabilities of language models
Build and share delightful machine learning apps, all in Python. 🌟 Star to support our work!
OBS Studio - Free and open source software for live streaming and screen recording
Implementation of Dreambooth (https://arxiv.org/abs/2208.12242) with Stable Diffusion
A collection of resources and papers on Diffusion Models
Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.
LICEcap simple animated screen capture tool for Windows and OS X
A comprehensive machine learning repository containing 30+ notebooks on different concepts, algorithms and techniques.
A curated list of awesome Deep Learning tutorials, projects and communities.
Behavioral "black-box" testing for recommender systems