Uploaded December 2021 | Updated September 2026, 2 weeks ago

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PyCaret is an open source, low-code machine learning library in Python that allows you to go from preparing your data to deploying your model within minutes in your choice of notebook environment.

In other words, 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 speeds up the experiment cycle exponentially and makes you more productive.

PyCaret is an alternate low-code library that can be used to replace hundreds of lines of code with few lines only.This Python package supports following Machine Learning (ML) models and frameworks:
- scikit-learn
- XGBoost
- LightGBM
- CatBoost
- spaCy
- Optuna
- Hyperopt
- Ray, and few more.

In this Demo I showed how to:
- Install PyCaret.
- Setup PyCaret environment in Jupyter Notebook
- Prepare data for analysis.
- Compare different ML models for the given dataset
- Analyze ML performance metrics
- Select the best ML model
- Check the model predictions
- Save the best model locally on your computer.

Links:
- Official PyCaret documentation: github.com/pycaret/pycaret
- Official PyCare Github repo: github.com/pycaret/pycaret

At the moment this video was recorded, there was PyCaret v.2.3 available. The project is updated very smartly and more interactive features will be available soon. Recommend to try it!