Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
---|---|---|---|---|---|---|---|---|---|---|
Keras | 59,402 | 578 | 10 hours ago | 80 | June 27, 2023 | 86 | apache-2.0 | Python | ||
Deep Learning for humans | ||||||||||
Scikit Learn | 55,918 | 18,944 | 9,755 | 10 hours ago | 71 | June 30, 2023 | 2,263 | bsd-3-clause | Python | |
scikit-learn: machine learning in Python | ||||||||||
Ml For Beginners | 53,615 | 19 hours ago | 8 | mit | HTML | |||||
12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all | ||||||||||
Made With Ml | 34,182 | 2 days ago | 5 | May 15, 2019 | 2 | mit | Jupyter Notebook | |||
Learn how to design, develop, deploy and iterate on production-grade ML applications. | ||||||||||
Ray | 27,746 | 80 | 298 | 13 hours ago | 87 | July 24, 2023 | 3,410 | 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. | ||||||||||
Streamlit | 27,271 | 17 | 898 | 21 hours ago | 204 | July 20, 2023 | 653 | apache-2.0 | Python | |
Streamlit — A faster way to build and share data apps. | ||||||||||
Spacy | 27,161 | 1,533 | 1,198 | 13 hours ago | 222 | July 07, 2023 | 96 | mit | Python | |
💫 Industrial-strength Natural Language Processing (NLP) in Python | ||||||||||
Data Science Ipython Notebooks | 25,242 | 3 months ago | 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. | ||||||||||
Applied Ml | 24,714 | 16 days ago | 3 | mit | ||||||
📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production. | ||||||||||
Lightning | 24,668 | 7 | 620 | 2 days ago | 253 | July 25, 2023 | 683 | apache-2.0 | Python | |
Deep learning framework to train, deploy, and ship AI products Lightning fast. |
The fastest way to build and share data apps.
Streamlit lets you turn data scripts into shareable web apps in minutes, not weeks. It’s all Python, open-source, and free! And once you’ve created an app you can use our Community Cloud platform to deploy, manage, and share your app!
pip install streamlit
streamlit hello
Streamlit can also be installed in a virtual environment on Windows, Mac, and Linux.
Streamlit makes it incredibly easy to build interactive apps:
import streamlit as st
x = st.slider('Select a value')
st.write(x, 'squared is', x * x)
Streamlit's simple and focused API lets you build incredibly rich and powerful tools. This demo project lets you browse the entire Udacity self-driving-car dataset and run inference in real-time using the YOLO object detection net.
The complete demo is implemented in less than 300 lines of Python. In fact, the app contains only 23 Streamlit calls which illustrates all the major building blocks of Streamlit. You can try it right now at share.streamlit.io/streamlit/demo-self-driving.
Streamlit's GitHub badge helps others find and play with your Streamlit app.
Once you deploy your app, you can embed this badge right into your GitHub readme.md as follows:
[](https://share.streamlit.io/yourGitHubName/yourRepo/yourApp/)
With Community Cloud you can deploy, manage, and share your apps with the world, directly from Streamlit — all for free. Sign-up here.
Streamlit is completely free and open-source and licensed under the Apache 2.0 license.