Welcome to PyCaret


PyCaret is an open-source, low-code machine learning library in Python that aims to reduce the cycle time from hypothesis to insights. It is well suited for seasoned data scientists who want to increase the productivity of their ML experiments by using PyCaret in their workflows or for citizen data scientists and those new to data science with little or no background in coding. PyCaret allows you to go from preparing your data to deploying your model within seconds using your choice of notebook environment.

PyCaret 2.2 is now available. Click here to see release notes.  Click Here to see the latest documentation.

PyCaret 2.2

PyCaret 2.2 is now available. Click here to see the release notes and learn more about what’s new in 2.2 and how it can help you automate your machine learning workflows.

Install PyCaret

Installing PyCaret is the first step to building your model. You can install and use PyCaret within any Notebook environment, be it Jupyter Notebook, Azure Notebooks or Google Colab.

Functions

Functions are a set of actions, that are naturally constructed and consistent across all modules. To perform modeling in PyCaret, you must learn how to use functions to achieve your end goal. Learn More

Preprocessing

PyCaret provides a library of over 25 preprocessing steps that can be used to prepare your data. From feature transformation to advanced feature engineering, PyCaret automates it all. Learn More

Contribute

PyCaret is an open-source project and is always looking for contributors. There are many ways to contribute to PyCaret with the most common one being the contribution of code. Learn More