PyCaret is an open-source, low-code machine learning library in Python that automates machine learning workflows. It is an end-to-end machine learning and model management tool that exponentially speeds up the experiment cycle and makes you more productive.
Compared with the other open-source machine learning libraries, PyCaret is an alternate low-code library that can replace hundreds of lines of code with a few lines only. This makes experiments exponentially faster and more efficient. PyCaret is essentially a Python wrapper around several machine learning libraries and frameworks such as scikit-learn, XGBoost, LightGBM, CatBoost, spaCy, Optuna, Hyperopt, Ray, and a few more.
The design and simplicity of PyCaret are 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 technical expertise.
references:
https://www.datacamp.com/tutorial/guide-for-automating-ml-workflows-using-pycaret
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