Welcome to PyCaret

PyCaret is a low-code, end-to-end ML and model management tool for the experimentation cycle.

PyCaret provides low-code APIs for state-of-art AI frameworks such as scikit-learn, XGBoost, LightGBM, CatBoost, and more.

The design and simplicity of PyCaret is inspired by the emerging role of citizen data scientists, a term first used by Gartner. Citizen Data Scientists are power users who can perform both simple and moderately sophisticated analytical tasks that would previously have required more expertise. Seasoned data scientists are often difficult to find and expensive to hire but citizen data scientists can be an effective way to mitigate this gap and address data-related challenges in the business setting.

Key Links and Resources:

• Release Notes

• Example Notebooks

• LinkedIn

• Contribute

Citing PyCaret:

If you’re citing PyCaret in research or scientific paper, please cite this page as the resource. PyCaret’s first stable release 1.0.0 was made publicly available in April 2020.

A formatted version of the citation would look like this:

@Manual{PyCaret,
  author  = {Moez Ali},
  title   = {PyCaret: An open source, low-code machine learning library in Python},
  year    = {2020},
  month   = {April},
  note    = {PyCaret version 1.0.0},
  url     = {https://www.pycaret.org}
}

We are appreciated that PyCaret has been increasingly referred and cited in scientific works. See all citations here.