LightAutoML VS jupyter

Compare LightAutoML vs jupyter and see what are their differences.

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LightAutoML jupyter
1 13
767 14,692
- 0.5%
9.2 7.5
almost 2 years ago 6 days ago
Python Python
Apache License 2.0 BSD 3-clause "New" or "Revised" License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

LightAutoML

Posts with mentions or reviews of LightAutoML. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-07-24.

jupyter

Posts with mentions or reviews of jupyter. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-04-24.

What are some alternatives?

When comparing LightAutoML and jupyter you can also consider the following projects:

nteract - πŸ“˜ The interactive computing suite for you! ✨

cookiecutter-data-science - A logical, reasonably standardized, but flexible project structure for doing and sharing data science work.

pyodide - Pyodide is a Python distribution for the browser and Node.js based on WebAssembly

FEDOT - Automated modeling and machine learning framework FEDOT

nni - An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.

vscode-python - Python extension for Visual Studio Code

quokka - Repository for Quokka.js questions and issues

Kedro - Kedro is a toolbox for production-ready data science. It uses software engineering best practices to help you create data engineering and data science pipelines that are reproducible, maintainable, and modular.

notebook - Jupyter Interactive Notebook

typescript-notebook - Run JavaScript and TypeScript in node.js within VS Code notebooks with excellent support for debugging, tensorflowjs visulizations, plotly, danfojs, etc

mathematica - Lean-independent implementation of the MM-Lean link