Top AI Repos — open-source AI, indexed and scored
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
A curated list of awesome Deep Learning (DL) for Natural Language Processing (NLP) resources
| Date | Stars |
|---|---|
| 2026-08-04 | 1309 |
| 2026-08-06 | 1309 |
| 2026-08-13 | 1308 |
| 2026-08-18 | 1308 |
| 2026-08-20 | 1309 |
| 2026-08-28 | 1310 |
| 2026-08-30 | 1311 |
| 2026-09-01 | 1312 |
| 2026-09-03 | 1311 |
| 2026-09-04 | 1311 |
| 2026-09-05 | 1312 |
| 2026-09-12 | 1312 |
| 2026-09-13 | 1311 |
| 2026-10-09 | 1310 |
| 2026-10-10 | 1311 |
| 2026-10-20 | 1311 |
| 2026-10-29 | 1311 |
| 2026-10-30 | 1310 |
| 2026-10-31 | 1311 |
| 2026-11-03 | 1311 |
| 2026-11-04 | 1311 |
Today
— stars today
This week
— stars this week
This month
— stars this month
Momentum
0.0
growth rate 0.00%/day
Awesome Deep Learning for Natural Language Processing (NLP) [](https://github.com/sindresorhus/awesome) ==== Table of Contents ---- - __[Courses](#courses)__ - __[Books](#books)__ - __[Tutorials](#tutorials)__ - __[Talks / Lectures](#talks)__ - __[Frameworks / Models](#frameworks)__ - __[Papers](#papers)__ - __[Blog Posts](#blog-posts)__ - __[Datasets](#datasets)__ - __[Word Embeddings / Word Vectors](#word-embeddings)__ - __[Contributing](#contributing)__ Courses ---- 1. NLP with Deep Learning / CS224N from Stanford (Winter 2019) - [Course homepage](http://web.stanford.edu/class/cs224n/index.html) A complete survey of the field with videos, lecture slides, and sample student projects. - [Course lectures](https://www.youtube.com/watch?v=8rXD5-xhemo&list=PLoROMvodv4rOhcuXMZkNm7j3fVwBBY42z) Video playlist. - [Previous course notes](https://github.com/stanfordnlp/cs224n-winter17-notes) Probably the best "book" on DL for NLP. - [Course code](https://github.com/DSKSD/DeepNLP-models-Pytorch) Pytorch implementations of various Deep NLP models in cs-224n. 1. Neural Networks for NLP from Carnegie Mellon University - [Course homepage](http://phontron.com/class/nn4nlp2017/) - [Course lectures](https://www.youtube.com/user/neubig/videos) - [Course code](https://github.com/neubig/nn4nlp2017-code/) 1. Deep Learning for Natural Language Processing from University of Oxford and DeepMind - [Course homepage](https://www.cs.ox.ac.uk/teaching/courses/2016-2017/dl/) - [Course slides](https://github.com/oxford-cs-deepnlp-2017/lectures) - [Course lectures](https://www.youtube.com/playlist?list=PL613dYIGMXoZBtZhbyiBqb0QtgK6oJbpm) Books ----- 1. [Deep Learning with Text: Natural Language Processing (Almost) from Scratch with Python and spaCy](https://www.amazon.com/Deep-Learning-Text-Approach-Processing/dp/1491984414) by Patrick Harrison and Matthew Honnibal 1. [Neural Network Methods in Natural Language Processing](https://www.amazon.com/gp/product/1627052984) by Yoav Goldberg and Graeme Hirst 1. [Deep Learning in Natural Language Processing](http://www.springer.com/us/book/9789811052088) by Li Deng and Yang Liu 1. [The Math Behind Artificial Intelligence: A Guide to AI Foundations [Full Book]](https://www.freecodecamp.org/news/the-math-behind-artificial-intelligence-book/) - Free book teaching the math behind AI with plain English explanations and Python code examples 1. [Natural Language Processing in Action](https://www.manning.com/books/natural-language-processing-in-action) by Hobson Lane, Cole Howard, and Hannes Hapke 1. Deep Learning: Natural Language Processing in Python by The LazyProgrammer (Kindle only) 1. [Word2Vec and Word Embeddings in Python and Theano](https://www.amazon.com/Deep-Learning-Language-Processing-Embeddings-ebook/dp/B01KQ0ZN0A) 1. [From Word2Vec to GLoVe in Python and Theano](https://www.amazon.com/Deep-Learning-Language-Processing-Word2Vec-ebook/dp/B01KRBOO4Y/) 1. [Recursive Neural Networks: Recursive Neural (Tensor) Networks in Theano](https://www.amazon.com/Deep-Learning-Language-Processing-Recursive-ebook/dp/B01KS5AEXO) 1. [Applied Natural Language Processing with Python](https://www.amazon.ca/Applied-Natural-Language-Processing-Python/dp/1484237323) by Taweh Beysolow II 1. [Deep Learning Cookbook](https://www.amazon.ca/Deep-Learning-Cookbook-Practical-Recipes/dp/149199584X) by Douwe Osinga 1. [Deep Learning for Natural Language Processing: Creating Neural Networks with Python](https://www.amazon.ca/Deep-Learning-Natural-Language-Processing/dp/148423684X) by Palash Goyal, Sumit Pandey, Karan Jain 1. [Machine Learning for Text](https://www.amazon.ca/Machine-Learning-Text-Charu-Aggarwal/dp/3319735306) by Charu C. Aggarwal 1. [Natural Language Processing with TensorFlow](https://www.amazon.ca/Natural-Language-Processing-TensorFlow-language-ebook/dp/B077Q3VZFR) by Thushan Ganegedara 1. [fastTex
Excerpt of 17,796 characters
Read on GitHub85
4
Stjepan Jureković · Manning Publication · Croatia
2
2
Vanshika Gupta
1
Tiago monteiro · Northeastern University · United States
1
Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:ecd8ce058c27ab19, desc:natural language processing