PyCaret 3.0
A Python-based, open-source library for low-code machine learning PyCaret is a Python library that offers low-code solutions for machine learning, streamlining the process by automating workflows. It serves as a comprehensive tool for machine learning and model management, significantly accelerating the experimental cycle and enhancing productivity. In comparison to other open-source machine learning libraries, PyCaret stands out as a low-code alternative that can condense hundreds of lines of code into just a few, making experiments remarkably quick and efficient. Essentially, PyCaret acts as a Python interface for several machine learning libraries and frameworks, including but not limited to scikit-learn, XGBoost, LightGBM, CatBoost, spaCy, Optuna, Hyperopt, and Ray. The architecture and user-friendliness of PyCaret are influenced by the rising prominence of citizen data scientists, a concept initially introduced by Gartner. These citizen data scientists are power users capable of executing both basic and moderately complex analytical tasks that would have previously necessitated more technical skills.
https://pycaret.gitbook.io/docs/get-started/quickstart
