PyCaret is an open source, `low-code` machine learning library in Python that aims to reduce the cycle time from hypothesis to insights. It enables data scientists and analysts to perform iterative end-to-end data science experiments efficiently and allows them to reach conclusions faster due to far less time spent in coding. PyCaret is essentially a Python wrapper around several machine learning libraries and frameworks such as scikit-learn, XGBoost, Microsoft LightGBM, spaCy and many more.
PyCaret is an open source, `low-code` machine learning library in Python that aims to reduce the cycle time from hypothesis to insights. It enables data scientists and analysts to perform iterative end-to-end data science experiments efficiently and allows them to reach conclusions faster due to far less time spent in coding. PyCaret is essentially a Python wrapper around several machine learning libraries and frameworks such as scikit-learn, XGBoost, Microsoft LightGBM, spaCy and many more.
In comparison with the other open source machine learning libraries, PyCaret is an alternate `low-code` machine learning solution that allows data scientists to perform end-to-end iterative experiments and enhances their ability to perform simple to complex operations without the need to write and maintain extra lines of code.
In comparison with the other open source machine learning libraries, PyCaret is an alternate `low-code` machine learning solution that allows data scientists to perform end-to-end iterative experiments and enhances their ability to perform simple to complex operations without the need to write and maintain extra lines of code.
