Starred repositories
436
stars
written in Python
Clear filter
☁️ Build multimodal AI applications with cloud-native stack
Best Practices on Recommendation Systems
Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
State-of-the-Art Text Embeddings
An advanced Twitter scraping & OSINT tool written in Python that doesn't use Twitter's API, allowing you to scrape a user's followers, following, Tweets and more while evading most API limitations.
A very simple framework for state-of-the-art Natural Language Processing (NLP)
music library manager and MusicBrainz tagger
Python package built to ease deep learning on graph, on top of existing DL frameworks.
An open source implementation of CLIP.
Postgres CLI with autocompletion and syntax highlighting
An open-source NLP research library, built on PyTorch.
dbt enables data analysts and engineers to transform their data using the same practices that software engineers use to build applications.
💡 All-in-one open-source AI framework for semantic search, LLM orchestration and language model workflows
Cleanlab's open-source library is the standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.
Minimal and clean examples of machine learning algorithms implementations
Always know what to expect from your data.
Kedro is a toolbox for production-ready data science. It uses software engineering best practices to help you create data engineering and data science pipelines that are reproducible, maintainable,…
Open source annotation tool for machine learning practitioners.
🌸 Run LLMs at home, BitTorrent-style. Fine-tuning and inference up to 10x faster than offloading
Simple, Pythonic, text processing--Sentiment analysis, part-of-speech tagging, noun phrase extraction, translation, and more.
A logical, reasonably standardized, but flexible project structure for doing and sharing data science work.
A unified framework for machine learning with time series
Plumb a PDF for detailed information about each char, rectangle, line, et cetera — and easily extract text and tables.
A python library for user-friendly forecasting and anomaly detection on time series.