dunovank / jupyter-themesView external linksLinks
Custom Jupyter Notebook Themes
☆9,827Jun 22, 2025Updated 7 months ago
Alternatives and similar repositories for jupyter-themes
Users that are interested in jupyter-themes are comparing it to the libraries listed below
Sorting:
- A collection of various notebook extensions for Jupyter☆5,286Jul 4, 2024Updated last year
- JupyterLab computational environment.☆15,007Feb 11, 2026Updated last week
- Jupyter Notebooks as Markdown Documents, Julia, Python or R scripts☆7,114Jan 25, 2026Updated 3 weeks ago
- 📘 The interactive computing suite for you! ✨☆6,274Dec 30, 2023Updated 2 years ago
- Plotting library for IPython/Jupyter notebooks☆3,682Jan 23, 2026Updated 3 weeks ago
- Declarative visualization library for Python☆10,264Updated this week
- RISE: "Live" Reveal.js Jupyter/IPython Slideshow Extension☆3,738Oct 29, 2023Updated 2 years ago
- Python Data Science Handbook: full text in Jupyter Notebooks☆46,737Jun 26, 2024Updated last year
- A Fast, Extensible Progress Bar for Python and CLI☆30,952Updated this week
- Deep Learning for humans☆63,764Updated this week
- [RETIRED] See Voilà as a supported replacement☆978Oct 26, 2019Updated 6 years ago
- Multi-user server for Jupyter notebooks☆8,225Feb 9, 2026Updated last week
- Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce,…☆28,857Mar 20, 2024Updated last year
- Apply custom CSS styling to your jupyter notebooks☆330Aug 22, 2018Updated 7 years ago
- 📚 Parameterize, execute, and analyze notebooks☆6,373Jan 5, 2026Updated last month
- Interactive Widgets for the Jupyter Notebook☆3,296Nov 7, 2025Updated 3 months ago
- Modin: Scale your Pandas workflows by changing a single line of code☆10,357Feb 10, 2026Updated last week
- Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on sing…☆28,006Updated this week
- Parallel computing with task scheduling☆13,738Feb 5, 2026Updated last week
- 1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.☆13,376Feb 2, 2026Updated 2 weeks ago
- Python Fire is a library for automatically generating command line interfaces (CLIs) from absolutely any Python object.☆28,108Feb 1, 2026Updated 2 weeks ago
- An interactive grid for sorting, filtering, and editing DataFrames in Jupyter notebooks☆3,088Jan 12, 2024Updated 2 years ago
- aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-firs…☆28,477Jun 25, 2024Updated last year
- Ready-to-run Docker images containing Jupyter applications☆8,412Feb 8, 2026Updated last week
- Interactive Data Visualization in the browser, from Python☆20,345Updated this week
- Jupyter metapackage for installation and documentation☆15,286Dec 17, 2025Updated 2 months ago
- A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.☆10,048Sep 11, 2025Updated 5 months ago
- Tools for diffing and merging of Jupyter notebooks.☆2,813Updated this week
- 💫 Industrial-strength Natural Language Processing (NLP) in Python☆33,201Nov 27, 2025Updated 2 months ago
- A curated list of awesome JupyterLab extensions and resources☆2,616Nov 3, 2022Updated 3 years ago
- Voilà turns Jupyter notebooks into standalone web applications☆5,898Updated this week
- A jupyter notebook serverextension providing config interfaces for nbextensions.☆989Jun 5, 2024Updated last year
- The fastai deep learning library☆27,845Updated this week
- Visual analysis and diagnostic tools to facilitate machine learning model selection.☆4,393Feb 19, 2025Updated 11 months ago
- TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)☆43,802Jul 26, 2024Updated last year
- Models and examples built with TensorFlow☆77,687Updated this week
- scikit-learn: machine learning in Python☆64,973Feb 10, 2026Updated last week
- Jupyter Interactive Notebook☆12,947Updated this week
- A game theoretic approach to explain the output of any machine learning model.☆25,023Updated this week