| keras-team/keras |
60,198 |
|
0 |
697 |
about 2 years ago |
87 |
December 06, 2023 |
183 |
apache-2.0 |
Python |
| Deep Learning for humans |
| 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. |
| Lightning-AI/pytorch-lightning |
30,802 |
|
0 |
0 |
2 months ago |
0 |
|
713 |
apache-2.0 |
Python |
| Pretrain, finetune ANY AI model of ANY size on 1 or 10,000+ GPUs with zero code changes. |
| streamlit/streamlit |
29,794 |
|
17 |
1,228 |
about 2 years ago |
212 |
November 30, 2023 |
712 |
apache-2.0 |
Python |
| Streamlit — A faster way to build and share data apps. |
| ray-project/ray |
29,596 |
|
80 |
363 |
about 2 years ago |
95 |
December 04, 2023 |
3,528 |
apache-2.0 |
Python |
| Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads. |
| 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 |
| AMAI-GmbH/AI-Expert-Roadmap |
27,583 |
|
0 |
0 |
over 2 years ago |
0 |
|
17 |
mit |
JavaScript |
| Roadmap to becoming an Artificial Intelligence Expert in 2022 |
| gradio-app/gradio |
25,823 |
|
1 |
229 |
about 2 years ago |
534 |
December 05, 2023 |
452 |
apache-2.0 |
Python |
| Build and share delightful machine learning apps, all in Python. 🌟 Star to support our work! |
| donnemartin/data-science-ipython-notebooks |
25,668 |
|
0 |
0 |
over 2 years ago |
0 |
|
34 |
other |
Python |
| Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines. |
| 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. |
