Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
---|---|---|---|---|---|---|---|---|---|---|
Ml For Beginners | 60,883 | 5 days ago | 10 | mit | HTML | |||||
12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all | ||||||||||
Keras | 59,925 | 690 | a day ago | 86 | November 28, 2023 | 123 | apache-2.0 | Python | ||
Deep Learning for humans | ||||||||||
Scikit Learn | 56,600 | 18,944 | 11,480 | a day ago | 73 | October 23, 2023 | 2,241 | bsd-3-clause | Python | |
scikit-learn: machine learning in Python | ||||||||||
Made With Ml | 34,597 | 2 months ago | 5 | May 15, 2019 | 4 | mit | Jupyter Notebook | |||
Learn how to design, develop, deploy and iterate on production-grade ML applications. | ||||||||||
Ray | 28,892 | 80 | 362 | a day ago | 94 | December 01, 2023 | 3,474 | 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 | 28,825 | 17 | 1,201 | a day ago | 212 | November 30, 2023 | 702 | apache-2.0 | Python | |
Streamlit — A faster way to build and share data apps. | ||||||||||
Spacy | 27,699 | 1,533 | 1,367 | 4 days ago | 226 | October 16, 2023 | 90 | mit | Python | |
💫 Industrial-strength Natural Language Processing (NLP) in Python | ||||||||||
Data Science Ipython Notebooks | 25,668 | 2 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. | ||||||||||
Pytorch Lightning | 25,319 | 3 hours ago | 706 | apache-2.0 | Python | |||||
Deep learning framework to train, finetune and deploy AI models | ||||||||||
Applied Ml | 24,828 | 2 months ago | 3 | mit | ||||||
📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production. |
A next-generation Python notebook: explore data, build tools, deploy apps!
marimo is a next-generation Python notebook where every notebook is also shareable as an interactive web app: explore data, run experiments, build tools, and deploy apps, all from one seamless environment.
pip install marimo && marimo tutorial intro
Watch the animated GIF as a video at this link.
When you run a cell, marimo automatically runs all other cells that depend on it (like a spreadsheet!). This reactivity, along with marimo's built-in interactive UI elements, lets you make powerful notebooks and apps that make your data tangible.
Highlights.
.py
filesInstallation. In a terminal, run
pip install marimo
marimo tutorial intro
You should see a tutorial notebook in your browser.
Create notebooks. Create an empty notebook with
marimo edit
or create/edit a notebook with a given name with
marimo edit your_notebook.py
marimo
in your notebooks to use
interactive elements, like sliders, dropdowns, tables, and more.See our docs to learn more, including how to layout outputs in tabs, rows, columns, and more.
Run apps. Run your notebook as a web app, with Python code hidden and uneditable:
marimo run your_notebook.py
This app is deployed on marimo cloud, our unified platform for deploying and sharing notebooks and apps.
Automatically convert Jupyter notebooks. Automatically translate Jupyter notebooks to marimo notebooks:
marimo convert your_notebook.ipynb > your_notebook.py
Tutorials. List all tutorials:
marimo tutorial --help
GitHub Copilot. The marimo editor natively supports GitHub Copilot. Enable it via the settings menu in the marimo editor.
VS Code extension. If you prefer VS Code over terminal, try our VS Code extension.
marimo is easy to get started with, with lots of room for power users. You can build powerful apps, including data labeling tools, embedding visualizers, model evaluation dashboards, and more, with surprisingly little code.
Examples are available in the examples/
directory.
We've deployed many of these examples at our public
gallery; try them out!
Ready to learn more? Check out our docs!
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Tutorial | Inputs | Plots | Layout |
See the FAQ at our docs.
We appreciate all contributions! You don't need to be an expert to help out. Please see CONTRIBUTING.md for more details on how to get started.
Questions? Reach out to us on Discord.
We're building a community. Come hang out with us!