| huggingface/transformers |
119,240 |
|
64 |
2,484 |
about 2 years ago |
125 |
November 15, 2023 |
946 |
apache-2.0 |
Python |
| 🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX. |
| d2l-ai/d2l-zh |
53,401 |
|
1 |
1 |
about 2 years ago |
51 |
August 18, 2023 |
65 |
apache-2.0 |
Python |
| 《动手学深度学习》：面向中文读者、能运行、可讨论。中英文版被70多个国家的500多所大学用于教学。 |
| GokuMohandas/Made-With-ML |
34,775 |
|
0 |
0 |
over 2 years ago |
5 |
May 15, 2019 |
6 |
mit |
Jupyter Notebook |
| Learn how to design, develop, deploy and iterate on production-grade ML applications. |
| explosion/spaCy |
28,084 |
|
1,533 |
1,367 |
about 2 years ago |
226 |
October 16, 2023 |
103 |
mit |
Python |
| 💫 Industrial-strength Natural Language Processing (NLP) in Python |
| microsoft/AI-For-Beginners |
26,668 |
|
0 |
0 |
about 2 years ago |
0 |
|
64 |
mit |
Jupyter Notebook |
| 12 Weeks, 24 Lessons, AI for All! |
| eugeneyan/applied-ml |
24,828 |
|
0 |
0 |
over 2 years ago |
0 |
|
3 |
mit |
|
| 📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production. |
| sebastianruder/NLP-progress |
22,082 |
|
0 |
0 |
over 2 years ago |
0 |
|
52 |
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-ai/d2l-en |
20,613 |
|
0 |
0 |
about 2 years ago |
2 |
November 13, 2022 |
115 |
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. |
| AI4Finance-Foundation/FinGPT |
18,673 |
|
0 |
0 |
2 months ago |
2 |
October 20, 2023 |
57 |
mit |
Jupyter Notebook |
| FinGPT: Open-Source Financial Large Language Models! Revolutionize 🔥 We release the trained model on HuggingFace. |
| huggingface/datasets |
17,925 |
|
9 |
760 |
about 2 years ago |
76 |
November 16, 2023 |
665 |
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 |
