Jupyter
The repository contains script and notebook related to Statistics, Machine learning, Neural network, Deep learning, NLP, Numerical methods, and Automation.
Install / Use
/learn @TheAlgorithms/JupyterREADME
The Algorithms - Jupyter
Getting started
You can run and edit the algorithms or contribute to them using Gitpod.io, a free online development environment, with a single click.
Contributing New Algorithms
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Make your pull requests to be specific and focused. Instead of contributing "several algorithms" all at once contribute them all one by one separately (i.e. one pull request for "Logistic Regression", another one for "K-Means", and so on).
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Every new algorithm must have:
- Source code with comments and readable namings
- Math being explained in README.md along with the code
- Jupyter demo notebook with an example of how this new algorithm may be applied
If you're adding new datasets they need to be saved in the /data folder. CSV files are preferable. The size of the file should not be greater than 30Mb.
Contributing
Before removing any bug, or adding new algorithms please read our Contribution Guidelines and our Code of Conduct.
License
All the code is licensed under the MIT License
