|Project Name||Stars||Downloads||Repos Using This||Packages Using This||Most Recent Commit||Total Releases||Latest Release||Open Issues||License||Language|
|Transformers||112,535||64||1,869||12 hours ago||114||July 18, 2023||844||apache-2.0||Python|
|🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.|
|D2l Zh||48,273||1||1||13 days ago||47||December 15, 2022||48||apache-2.0||Python|
|Made With Ml||34,217||a day ago||5||May 15, 2019||4||mit||Jupyter Notebook|
|Learn how to design, develop, deploy and iterate on production-grade ML applications.|
|Spacy||27,226||1,533||1,198||17 hours ago||222||July 07, 2023||95||mit||Python|
|💫 Industrial-strength Natural Language Processing (NLP) in Python|
|Applied Ml||24,714||21 days ago||3||mit|
|📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.|
|Nlp Progress||21,719||3 months ago||51||mit||Python|
|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.|
|D2l En||18,967||a month ago||2||November 13, 2022||95||other||Python|
|Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.|
|Ai For Beginners||17,350||22 days ago||32||mit||Jupyter Notebook|
|12 Weeks, 24 Lessons, AI for All!|
|Datasets||17,201||9||540||16 hours ago||69||July 31, 2023||592||apache-2.0||Python|
|🤗 The largest hub of ready-to-use datasets for ML models with fast, easy-to-use and efficient data manipulation tools|
|Rasa||17,031||32||33||13 hours ago||341||July 25, 2023||130||apache-2.0||Python|
|💬 Open source machine learning framework to automate text- and voice-based conversations: NLU, dialogue management, connect to Slack, Facebook, and more - Create chatbots and voice assistants|
NLTK -- the Natural Language Toolkit -- is a suite of open source Python modules, data sets, and tutorials supporting research and development in Natural Language Processing. NLTK requires Python version 3.7, 3.8, 3.9, 3.10 or 3.11.
For documentation, please visit nltk.org.
Do you want to contribute to NLTK development? Great! Please read CONTRIBUTING.md for more details.
See also how to contribute to NLTK.
Have you found the toolkit helpful? Please support NLTK development by donating to the project via PayPal, using the link on the NLTK homepage.
If you publish work that uses NLTK, please cite the NLTK book, as follows:
Bird, Steven, Edward Loper and Ewan Klein (2009). Natural Language Processing with Python. O'Reilly Media Inc.
Copyright (C) 2001-2023 NLTK Project
For license information, see LICENSE.txt.
AUTHORS.md contains a list of everyone who has contributed to NLTK.